Genetic polymorphisms associated with cardiovascular disorders and drug response, methods of detection and uses thereof

ABSTRACT

The present invention is based on the discovery of genetic polymorphisms that are associated with cardiovascular disorders, particularly acute coronary events such as myocardial infarction and stroke, and genetic polymorphisms that are associated with responsiveness of an individual to treatment of cardiovascular disorders with statin. In particular, the present invention relates to nucleic acid molecules containing the polymorphisms, variant proteins encoded by such nucleic acid molecules, reagents for detecting the polymorphic nucleic acid molecules and proteins, and methods of using the nucleic acid and proteins as well as methods of using reagents for their detection.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. non-provisionalapplication Ser. No. 15/168,632, filed May 31, 2016, which is acontinuation application of U.S. non-provisional application Ser. No.14/045,416, filed Oct. 3, 2013, which is a divisional application ofU.S. non-provisional application Ser. No. 12/683,099, filed Jan. 6,2010, which is a divisional application of U.S. non-provisionalapplication Ser. No. 10/995,561, filed Nov. 24, 2004, which claimspriority to U.S. provisional application Ser. No. 60/524,882, filed Nov.26, 2003, and U.S. provisional application Ser. No. 60/568,219, filedMay 6, 2004, the contents of each of which are hereby incorporated byreference into this application.

FIELD OF THE INVENTION

The present invention is in the field of cardiovascular disorders anddrug response, particularly acute coronary events and statin treatmentof acute coronary events. In particular, the present invention relatesto specific single nucleotide polymorphisms (SNPs) in the human genome,and their association with acute coronary events and/or variability inthe responsiveness to statin treatment (including preventive treatment)between different individuals. The naturally-occurring SNPs disclosedherein can be used as targets for the design of diagnostic reagents andthe development of therapeutic agents, as well as for diseaseassociation and linkage analysis. In particular, the SNPs of the presentinvention are useful for, for example, identifying whether an individualis likely to experience an acute coronary event (either a first orrecurrent acute coronary event), for predicting the seriousness orconsequences of an acute coronary event in an individual, for prognosingan individual's recovery from an acute coronary event, for evaluatingthe likely response of an individual to statins for thetreatment/prevention of acute coronary events, for providing clinicallyimportant information for the prevention and/or treatment of acutecoronary events, and for screening and selecting therapeutic agents. TheSNPs disclosed herein are also useful for human identificationapplications. Methods, assays, kits, and reagents for detecting thepresence of these polymorphisms and their encoded products are provided.

BACKGROUND OF THE INVENTION

Cardiovascular Disorders and Response to Statin Treatment

Cardiovascular disorders include, for example, acute coronary eventssuch as myocardial infarction and stroke.

Myocardial Infarction

Myocardial infarction (MI) is the most common cause of mortality indeveloped countries. It is a multifactorial disease that involvesatherogenesis, thrombus formation and propagation. Thrombosis can resultin complete or partial occlusion of coronary arteries. The luminalnarrowing or blockage of coronary arteries reduces oxygen and nutrientsupply to the cardiac muscle (cardiac ischemia), leading to myocardialnecrosis and/or stunning. MI, unstable angina, or sudden ischemic deathare clinical manifestations of cardiac muscle damage. All threeendpoints are part of the Acute Coronary Syndrome since the underlyingmechanisms of acute complications of atherosclerosis are considered tobe the same.

Atherogenesis, the first step of pathogenesis of MI, is a complexinteraction between blood elements, mechanical forces, disturbed bloodflow, and vessel wall abnormality. On the cellular level, these includeendothelial dysfunction, monocytes/macrophages activation by modifiedlipoproteins, monocytes/macrophages migration into the neointima andsubsequent migration and proliferation of vascular smooth muscle cells(VSMC) from the media that results in plaque accumulation.

In recent years, an unstable (vulnerable) plaque was recognized as anunderlying cause of arterial thrombotic events and MI. A vulnerableplaque is a plaque, often not stenotic, that has a high likelihood ofbecoming disrupted or eroded, thus forming a thrombogenic focus. Twovulnerable plaque morphologies have been described. A first type ofvulnerable plaque morphology is a rupture of the protective fibrous cap.It can occur in plaques that have distinct morphological features suchas large and soft lipid pool with distinct necrotic core and thinning ofthe fibrous cap in the region of the plaque shoulders. Fibrous caps haveconsiderable metabolic activity. The imbalance between matrix synthesisand matrix degradation thought to be regulated by inflammatory mediatorscombined with VSMC apoptosis are the key underlying mechanisms of plaquerupture. A second type of vulnerable plaque morphology, known as “plaqueerosion”, can also lead to a fatal coronary thrombotic event. Plaqueerosion is morphologically different from plaque rupture. Eroded plaquesdo not have fractures in the plaque fibrous cap, only superficialerosion of the intima. The loss of endothelial cells can expose thethrombogenic subendothelial matrix that precipitates thrombus formation.This process could be regulated by inflammatory mediators. Thepropagation of the acute thrombi for both plaque rupture and plaqueerosion events depends on the balance between coagulation andthrombolysis. MI due to a vulnerable plaque is a complex phenomenon thatincludes: plaque vulnerability, blood vulnerability (hypercoagulation,hypothrombolysis), and heart vulnerability (sensitivity of the heart toischemia or propensity for arrhythmia).

Recurrent myocardial infarction (RMI) can generally be viewed as asevere form of MI progression caused by multiple vulnerable plaques thatare able to undergo pre-rupture or a pre-erosive state, coupled withextreme blood coagulability.

The incidence of MI is still high despite currently available preventivemeasures and therapeutic intervention. More than 1,500,000 people in theUS suffer acute MI each year (many without seeking help due tounrecognized MI), and one third of these people die. The lifetime riskof coronary artery disease events at age 40 years is 42.4% for men (onein two) and 24.9% for women (one in four) (Lloyd-Jones D M; Lancet, 1999353: 89-92).

The current diagnosis of MI is based on the levels of troponin I or Tthat indicate the cardiac muscle progressive necrosis, impairedelectrocardiogram (ECG), and detection of abnormal ventricular wallmotion or angiographic data (the presence of acute thrombi). However,due to the asymptomatic nature of 25% of acute MIs (absence of atypicalchest pain, low ECG sensitivity), a significant portion of MIs are notdiagnosed and therefore not treated appropriately (e.g., prevention ofrecurrent MIs).

Despite a very high prevalence and lifetime risk of MI, there are nogood prognostic markers that can identify an individual with a high riskof vulnerable plaques and justify preventive treatments. MI riskassessment and prognosis is currently done using classic risk factors orthe recently introduced Framingham Risk Index. Both of these assessmentsput a significant weight on LDL levels to justify preventive treatment.However, it is well established that half of all MIs occur inindividuals without overt hyperlipidemia. Hence, there is a need foradditional risk factors for predicting predisposition to MI.

Other emerging risk factors are inflammatory biomarkers such asC-reactive protein (CRP), ICAM-1, SAA, TNF α, homocysteine, impairedfasting glucose, new lipid markers (ox LDL, Lp-a, MAD-LDL, etc.) andpro-thrombotic factors (fibrinogen, PAI-1). Despite showing somepromise, these markers have significant limitations such as lowspecificity and low positive predictive value, and the need for multiplereference intervals to be used for different groups of people (e.g.,males-females, smokers-non smokers, hormone replacement therapy users,different age groups). These limitations diminish the utility of suchmarkers as independent prognostic markers for MI screening.

Genetics plays an important role in MI risk. Families with a positivefamily history of MI account for 14% of the general population, 72% ofpremature MIs, and 48% of all MIs (Williams R R, Am J Cardiology, 2001;87:129). In addition, replicated linkage studies have revealed evidenceof multiple regions of the genome that are associated with MI andrelevant to MI genetic traits, including regions on chromosomes 14, 2, 3and 7 (Broeckel U, Nature Genetics, 2002; 30: 210; Harrap S,Arterioscler Thromb Vasc Biol, 2002; 22: 874-878, Shearman A, HumanMolecular Genetics, 2000, 9; 9, 1315-1320), implying that genetic riskfactors influence the onset, manifestation, and progression of MI.Recent association studies have identified allelic variants that areassociated with acute complications of coronary heart disease, includingallelic variants of the ApoE, ApoA5, Lpa, APOCIII, and Klotho genes.

Genetic markers such as single nucleotide polymorphisms are preferableto other types of biomarkers. Genetic markers that are prognostic for MIcan be genotyped early in life and could predict individual response tovarious risk factors. The combination of serum protein levels andgenetic predisposition revealed by genetic analysis of susceptibilitygenes can provide an integrated assessment of the interaction betweengenotypes and environmental factors, resulting in synergisticallyincreased prognostic value of diagnostic tests.

Thus, there is an urgent need for novel genetic markers that arepredictive of predisposition to MI, particularly for individuals who areunrecognized as having a predisposition to MI. Such genetic markers mayenable prognosis of MI in much larger populations compared with thepopulations that can currently be evaluated by using existing riskfactors and biomarkers. The availability of a genetic test may allow,for example, appropriate preventive treatments for acute coronary eventsto be provided for susceptible individuals (such preventive treatmentsmay include, for example, statin treatments and statin dose escalation,as well as changes to modifiable risk factors), lowering of thethresholds for ECG and angiography testing, and allow adequatemonitoring of informative biomarkers.

Moreover, the discovery of genetic markers associated with MI willprovide novel targets for therapeutic intervention or preventivetreatments of MI, and enable the development of new therapeutic agentsfor treating MI and other cardiovascular disorders.

Stroke

Stroke is a prevalent and serious disease. Stroke is the most commoncause of disability, the second leading cause of dementia, and the thirdleading cause of mortality in the United States. It affects 4.7 millionindividuals in the United States, with 500,000 first attacks and 200,000recurrent cases yearly. Approximately one in four men and one in fivewomen aged 45 years will have a stroke if they live to their 85th year.About 25% of those who have a stroke die within a year. For that, strokeis the third leading cause of mortality in the United States and isresponsible for 170,000 deaths a year. Among those who survive thestroke attack, 30 to 50% do not regain functional independence.

Stroke occurs when an artery bringing oxygen or nutrients to the braineither ruptures, causing the hemorrhagic type of strokes, or getsoccluded, causing the thrombotic/embolic strokes that are collectivelyreferred to as ischemic strokes. In each case, a cascade of cellularchanges due to ischemia or increased cranial pressure leads to injuriesor death of the brain cells. In the United States, the majority (about80-90%) of strokes are ischemic, including 31% large-vessel thrombotic(also referred to as large-vessel occlusive disease), 20% small-vesselthrombotic (also referred to as small-vessel occlusive disease), and 32%embolic or cardiogenic (caused by a clot originating from elsewhere inthe body, e.g., from blood pooling due to atrial fibrillation, or fromcarotid artery stenosis). The ischemic form of stroke shares commonpathological etiology with atherosclerosis and thrombosis. 10-20% ofstrokes are of the hemorrhagic type, involving bleeding within or aroundthe brain. Bleeding within the brain is known as cerebral hemorrhage,which is often linked to high blood pressure. Bleeding into the meningessurrounding the brain is known as a subarachnoid hemorrhage, which couldbe caused by a ruptured cerebral aneurysm, an arteriovenousmalformation, or a head injury. The hemorrhagic strokes, although lessprevalent, pose a greater danger. Whereas about 8% of ischemic strokesresult in death within 30 days, about 38% of hemorrhagic strokes resultin death within the same time period.

Known risk factors for stroke can be divided into modifiable andnon-modifiable risk factors. Older age, male sex, black or Hispanicethnicity, and family history of stroke are non-modifiable risk factors.Modifiable risk factors include hypertension, smoking, increased insulinlevels, asymptomatic carotid disease, cardiac vessel disease, andhyperlipidemia. Information derived from the Dutch Twin Registryestimates the heritability of stroke as 0.32 for stroke death and 0.17for stroke hospitalization.

The acute nature of stroke leaves physicians with little time to preventor lessen the devastation of brain damage. Strategies to diminish theimpact of stroke include prevention and treatment with thrombolytic and,possibly, neuroprotective agents. The success of preventive measureswill depend on the identification of risk factors and means to modulatetheir impact.

Although some risk factors for stroke are not modifiable, such as ageand family history, other underlying pathology or risk factors of strokesuch as atherosclerosis, hypertension, smoking, diabetes, aneurysm, andatrial fibrillation, are chronic and amenable to effective life-style,medical, and surgical treatments. Early recognition of patients withthese risk factors, and especially those with a family history, with anon-invasive test of genetic markers will enable physicians to targetthe highest risk individuals for aggressive risk reduction.

Statin Treatment

Coronary heart disease (CHD) accounts for approximately two-thirds ofcardiovascular mortality in the United States, with CHD accounting for 1in every 5 deaths in 1998, which makes it the largest single cause ofmorality (American Heart Association. 2001 Heart and Stroke StatisticalUpdate. Dallas, Tex.: American Heart Association. 2000). Stroke is thethird leading cause of death, accounting for 1 of every 15 deaths.Reduction of coronary and cerebrovascular events and total mortality bytreatment with HMG-CoA reductase inhibitors (statins) has beendemonstrated in a number of randomized, double blinded, placebocontrolled prospective trials (Waters, D. D., What do the statin trialstell us? Clin Cardiol, 2001. 24(8 Suppl): p. 1113-7, Singh, B. K. and J.L. Mehta, Management of dyslipidemia in the primary prevention ofcoronary heart disease. Curr Opin Cardiol, 2002. 17(5): p. 503-11).These drugs have their primary effect through the inhibition of hepaticcholesterol synthesis, thereby upregulating LDL receptor in the liver.The resultant increase in LDL catabolism results in decreasedcirculating LDL, a major risk factor for cardiovascular disease. Inaddition, statins cause relatively small reductions in triglyceridelevels (5 to 10%) and elevations in HDL cholesterol (5 to 10%). In a 5year primary intervention trial (WOSCOPS), pravastatin decreasedclinical events 29% compared to placebo in hypercholesterolemicsubjects, achieving a 26% reduction in LDL-cholesterol (LDL-C)(Shepherd, J., et al., Prevention of coronary heart disease withpravastatin in men with hypercholesterolemia. West of Scotland CoronaryPrevention Study Group. N Engl J Med, 1995. 333(20): p. 1301-7). In asimilar primary prevention trial (AFCAPS/TexCAPS) (Downs, J. R., et al.,Primary prevention of acute coronary events with lovastatin in men andwomen with average cholesterol levels: results of AFCAPS/TexCAPS. AirForce/Texas Coronary Atherosclerosis Prevention Study. Jama, 1998.279(20): p. 1615-22) in which subjects with average cholesterol levelswere treated with lovastatin, LDL-C was reduced an average of 25% andevents decreased by 37%.

Secondary prevention statin trials include the CARE (Sacks, F. M., etal., The effect of pravastatin on coronary events after myocardialinfarction in patients with average cholesterol levels. Cholesterol andRecurrent Events Trial investigators. N Engl J Med, 1996. 335(14): p.1001-9) and LIPID (treatment with pravastatin) (Prevention ofcardiovascular events and death with pravastatin in patients withcoronary heart disease and a broad range of initial cholesterol levels.The Long-Term Intervention with Pravastatin in Ischaemic Disease (LIPID)Study Group. N Engl J Med, 1998. 339(19): p. 1349-57), and 4S (treatmentwith simvastatin) (Randomised trial of cholesterol lowering in 4444patients with coronary heart disease: the Scandinavian SimvastatinSurvival Study (4S). Lancet, 1994. 344(8934): p. 1383-9) studies. Inthese trials, clinical event risk was reduced from between 23% and 34%with achieved LDL-C lowering ranging between 25% and 35%.

In addition to LDL-lowering, a variety of potential non-lipid loweringeffects have been suggested to play a role in cardiovascular riskreduction by statins. These include anti-inflammatory effects on variousvascular cell types including foam cell macrophages, improvedendothelial responses, inhibition of platelet reactivity therebydecreasing hypercoaguability, and many others (Puddu, P., G. M. Puddu,and A. Muscari, Current thinking in statin therapy. Acta Cardiol, 2001.56(4): p. 225-31, Albert, M. A., et al., Effect of statin therapy onC-reactive protein levels: the pravastatin inflammation/CRP evaluation(PRINCE): a randomized trial and cohort study. Jama, 2001. 286(1): p.64-70, Rosenson, R. S., Non-lipid-lowering effects of statins onatherosclerosis. Curr Cardiol Rep, 1999. 1(3): p. 225-32, Dangas, G., etal., Pravastatin: an antithrombotic effect independent of thecholesterol-lowering effect. Thromb Haemost, 2000. 83(5): p. 688-92,Crisby, M., Modulation of the inflammatory process by statins. DrugsToday (Barc), 2003. 39(2): p. 137-43, Liao, J. K., Role of statinpleiotropism in acute coronary syndromes and stroke. Int J Clin PractSuppl, 2003(134): p. 51-7). However, because hypercholesterolemia is afactor in many of these additional pathophysiologic mechanisms that arereversed by statins, many of these statin benefits may be a consequenceof LDL lowering.

Statins as a class of drug are generally well tolerated. The most commonside effects include a variety of muscle-related complaints ormyopathies. While the incidence of muscle side effects are low, the mostserious side effect, myositis with rhabdomyolysis, is life threatening.This adverse effect has been highlighted by the recent withdrawal ofcerevastatin when the drug was found to be associated with a relativelyhigh level of rhabdomyolysis-related deaths. In addition, thedevelopment of a high dose sustained release formulation of simvastatinwas discontinued for rhabdomyolysis-related issues (Davidson, M. H., etal., The efficacy and six-week tolerability of simvastatin 80 and 160mg/day. Am J Cardiol, 1997. 79(1): p. 38-42).

Statins can be divided into two types according to their physicochemicaland pharmacokinetic properties. Statins such as lovastatin, simvastatin,atorvastatin, and cerevastatin are hydrophobic in nature and, as such,diffuse across membranes and thus are highly cell permeable. Hydrophilicstatins such as pravastatin are more polar, such that they requirespecific cell surface transporters for cellular uptake (Ziegler, K. andW. Stunkel, Tissue-selective action of pravastatin due to hepatocellularuptake via a sodium-independent bile acid transporter. Biochim BiophysActa, 1992. 1139(3): p. 203-9, Yamazaki, M., et al., Na(+)-independentmultispecific anion transporter mediates active transport of pravastatininto rat liver. Am J Physiol, 1993. 264(1 Pt 1): p. G36-44, Komai, T.,et al., Carrier-mediated uptake of pravastatin by rat hepatocytes inprimary culture. Biochem Pharmacol, 1992. 43(4): p. 667-70). The latterstatin utilizes a transporter, OATP2, whose tissue distribution isconfined to the liver and, therefore, they are relativelyhepato-specific inhibitors (Hsiang, B., et al., A novel human hepaticorganic anion transporting polypeptide (OATP2). Identification of aliver-specific human organic anion transporting polypeptide andidentification of rat and human hydroxymethylglutaryl-CoA reductaseinhibitor transporters. J Biol Chem, 1999. 274(52): p. 37161-8). Theformer statins, not requiring specific transport mechanisms, areavailable to all cells and they can directly impact a much broaderspectrum of cells and tissues. These differences in properties mayinfluence the spectrum of activities that each statin posesses.Pravastatin, for instance, has a low myopathic potential in animalmodels and myocyte cultures compared to other hydrophobic statins(Masters, B. A., et al., In vitro myotoxicity of the3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, pravastatin,lovastatin, and simvastatin, using neonatal rat skeletal myocytes.Toxicol Appl Pharmacol, 1995. 131(1): p. 163-74. Nakahara, K., et al.,Myopathy induced by HMG-CoA reductase inhibitors in rabbits: apathological, electrophysiological, and biochemical study. Toxicol ApplPharmacol, 1998. 152(1): p. 99-106, Reijneveld, J. C., et al.,Differential effects of 3-hydroxy-3-methylglutaryl-coenzyme A reductaseinhibitors on the development of myopathy in young rats. Pediatr Res,1996. 39(6): p. 1028-35).

Cardiovascular mortality in developed countries has decreased sharply inrecent decades (Tunstall-Pedoe, H., et al., Estimation of contributionof changes in coronary care to improving survival, event rates, andcoronary heart disease mortality across the WHO MONICA Projectpopulations. Lancet, 2000. 355(9205): p. 688-700). This is likely due tothe development and use of efficaceous hypertension, thrombolytic andlipid lowering therapies (Kuulasmaa, K., et al., Estimation ofcontribution of changes in classic risk factors to trends incoronary-event rates across the WHO MONICA Project populations. Lancet,2000. 355(9205): p. 675-87). Nevertheless, cardiovascular diseasesremain the major cause of death in industrialized countries, at least inpart due to the presence of highly prevalent risk factors andinsufficient treatment (Wong, M. D., et al., Contribution of majordiseases to disparities in mortality. N Engl J Med, 2002. 347(20): p.1585-92). Even with appropriate therapy, not all patients respondequally well to statin treatment. Despite the overwhelming evidence thatstatins decrease risk for cardiovascular disease, both in primary andsecondary intervention settings, statin therapy clearly only achievespartial risk reduction. While a decrease in risk of 23 to 37% seen inthe above trials is substantial and extremely important clinically, themajority of events still are not prevented by statin treatment. This isnot surprising given the complexity of cardiovascular disease etiology,which is influenced by genetics, environment, and a variety ofadditional risk factors including dyslipidemia, age, gender,hypertension, diabetes, obesity, and smoking. It is reasonable to assumethat all of these multi-factorial risks modify statin responses anddetermine the final benefit that each individual achieves from therapy.Furthermore, with the increasing incidence of Type 2 diabetes andobesity in Western countries (Flegal, K. M., et al., Prevalence andtrends in obesity among US adults, 1999-2000. Jama, 2002. 288(14): p.1723-7, Boyle, J. P., et al., Projection of diabetes burden through2050: impact of changing demography and disease prevalence in the U.S.Diabetes Care, 2001. 24(11): p. 1936-40), which are two major riskfactors for coronary artery disease, and the emergence of greatercardiovascular risk factors in the developing world (Yusuf, S., et al.,Global burden of cardiovascular diseases: Part II: variations incardiovascular disease by specific ethnic groups and geographic regionsand prevention strategies. Circulation, 2001. 104(23): p. 2855-64,Yusuf, S., et al., Global burden of cardiovascular diseases: part I:general considerations, the epidemiologic transition, risk factors, andimpact of urbanization. Circulation, 2001. 104(22): p. 2746-53), theneed for ever more effective treatment of CHD is predicted to steadilyincrease.

Thus, there is a growing need for ways to better identify people whohave the highest chance to benefit from statins, and those who have thelowest risk of developing side-effects. As indicated above, severemyopathies represent a significant risk for a low percentage of thepatient population. This would be particularly true for patients thatmay be treated more aggressively with statins in the future. There arecurrently at least three studies in progress that are investigatingwhether treatments aimed at lowering LDL-C to levels below current NCEPgoals by administering higher statin doses to patients further reducesCHD risk or provides additional cardiovascular benefits (reviewed inClark, L. T., Treating dyslipidemia with statins: the risk-benefitprofile. Am Heart J, 2003. 145(3): p. 387-96). It is possible that moreaggressive statin therapy than is currently standard practice willbecome the norm in the future if additional benefit is observed in suchtrials. More aggressive statin therapy will likely increase theincidence of the above adverse events as well as elevate the cost oftreatment. Thus, increased emphasis will be placed on stratifyingresponder and non-responder patients in order for maximum benefit-riskratios to be achieved at the lowest cost.

The Third Report of the Expert Panel on Detection, Evaluation andTreatment of High Blood Cholesterol in Adults (ATPIII) contains currentrecommendations for the management of high serum cholesterol (ExecutiveSummary of The Third Report of The National Cholesterol EducationProgram (NCEP) Expert Panel on Detection, Evaluation, And Treatment ofHigh Blood Cholesterol In Adults (Adult Treatment Panel III). Jama,2001. 285(19): p. 2486-97). A meta-analysis of 38 primary and secondaryprevention trials found that for every 10% decrease in serumcholesterol, CHD mortality was reduced by 15%. These guidelines tookinto account additional risk factors beyond serum cholesterol whenmaking recommendations for lipid lowering strategies. After consideringadditional risk factors and updated information on lipid loweringclinical trials, more patients are classified in the highest riskcategory of CHD or CHD risk equivalent than before and are recommendedto decrease their LDL to less than 100 mg/dl. As a consequence, moreaggressive therapy is recommended and drug therapy is recommended for36.5 million Americans. In implementing these recommendations,cost-effectiveness of treatments is a primary concern. In lower riskpopulations, the cost of reducing one event may exceed $125,000 comparedwith around $25,000 per event in a high-risk patient group (Singh, B. K.and J. L. Mehta, Management of dyslipidemia in the primary prevention ofcoronary heart disease. Curr Opin Cardiol, 2002. 17(5): p. 503-11). Thecost of preventing an event in a very low risk patient may exceed $1million. In the context of cost-containment, further risk stratificationof patients will help to avoid unnecessary treatment of patients. Inaddition to the various clinical endpoints that are currently consideredin determining overall risk, the determination of who and who not totreat with statins based on “statin response” genotypes couldsubstantially increase the precision of these determinations in thefuture.

Evidence from gene association studies is accumulating to indicate thatresponses to drugs are, indeed, at least partly under genetic control.As such, pharmacogenetics—the study of variability in drug responsesattributed to hereditary factors in different populations—maysignificantly assist in providing answers toward meeting this challenge(Roses, A. D., Pharmacogenetics and the practice of medicine. Nature,2000. 405(6788): p. 857-65, Mooser, V., et al., Cardiovascularpharmacogenetics in the SNP era. J Thromb Haemost, 2003. 1(7): p.1398-1402, Humma, L. M. and S. G. Terra, Pharmacogenetics andcardiovascular disease: impact on drug response and applications todisease management. Am. J. Health Syst Pharm, 2002. 59(13): p. 1241-52).Numerous associations have been reported between selected genotypes, asdefined by SNPs and other sequence variations and specific responses tocardiovascular drugs. Polymorphisms in several genes have been suggestedto influence responses to statins including CETP (Kuivenhoven, J. A., etal., The role of a common variant of the cholesteryl ester transferprotein gene in the progression of coronary atherosclerosis. TheRegression Growth Evaluation Statin Study Group. N Engl J Med, 1998.338(2): p. 86-93), beta-fibrinogen (de Maat, M. P., et al., −455G/Apolymorphism of the beta-fibrinogen gene is associated with theprogression of coronary atherosclerosis in symptomatic men: proposedrole for an acute-phase reaction pattern of fibrinogen. REGRESS group.Arterioscler Thromb Vasc Biol, 1998. 18(2): p. 265-71), hepatic lipase(Zambon, A., et al., Common hepatic lipase gene promoter variantdetermines clinical response to intensive lipid-lowering treatment.Circulation, 2001. 103(6): p. 792-8, lipoprotein lipase (Jukema, J. W.,et al., The Asp9 Asn mutation in the lipoprotein lipase gene isassociated with increased progression of coronary atherosclerosis.REGRESS Study Group, Interuniversity Cardiology Institute, Utrecht, TheNetherlands. Regression Growth Evaluation Statin Study. Circulation,1996. 94(8): p. 1913-8), glycoprotein IIIa (Bray, P. F., et al., Theplatelet Pl(A2) and angiotensin-converting enzyme (ACE) D allelepolymorphisms and the risk of recurrent events after acute myocardialinfarction. Am J Cardiol, 2001. 88(4): p. 347-52), stromelysin-1 (deMaat, M. P., et al., Effect of the stromelysin-1 promoter on efficacy ofpravastatin in coronary atherosclerosis and restenosis. Am J Cardiol,1999. 83(6): p. 852-6), and apolipoprotein E (Gerdes, L. U., et al., Theapolipoprotein epsilon4 allele determines prognosis and the effect onprognosis of simvastatin in survivors of myocardial infarction: asubstudy of the Scandinavian simvastatin survival study. Circulation,2000. 101(12): p. 1366-71, Pedro-Botet, J., et al., Apolipoprotein Egenotype affects plasma lipid response to atorvastatin in a genderspecific manner. Atherosclerosis, 2001. 158(1): p. 183-93).

Some of these variants were shown to effect clinical events while otherswere associated with changes in surrogate endpoints. The CETP variantalleles B1 and B2 were shown to be correlated with HDL cholesterollevels. Patients with B1B1 and B1B2 genotypes have lower HDL cholesteroland greater progression of angiographically-determined atherosclerosisthan B2B2 subjects when on placebo during the pravastatin REGRESSclinical trial. Furthermore, B1B1 and B1B2 had significantly lessprogression of atherosclerosis when on pravastatin whereas B2B2 patientsderived no benefit. Similarly, beta-fibrinogen promoter sequencevariants were also associated with disease progression and response topravastatin in the same study as were Stomelysin-1 promoter variants. Inthe Cholesterol and Recurrent Events (CARE) trial, a pravastatinsecondary intervention study, glycoprotein Ma variants were alsoassociated with clinical event response to pravastatin. In all of theabove cases, genetic subgroups of placebo-treated patients with CHD wereidentified who had increased risk for major coronary events. Treatmentwith pravastatin abolished the harmful effects associated with the“riskier” genotype, while having little effect on patients withgenotypes that were associated with less risk. Finally, the impact ofthe apolipoprotein ε4 genotype on prognosis and the response tosimvastatin or placebo was investigated in the Scandanavian SimvastatinSurvival Study (Pedro-Botet, J., et al., Apolipoprotein E genotypeaffects plasma lipid response to atorvastatin in a gender specificmanner. Atherosclerosis, 2001. 158(1): p. 183-93). Patients with atleast one apolipoprotein ε4 allele had a higher risk for all cause deaththan those lacking the allele. As was the case with pravastatintreatment, simvastatin reversed this detrimental effect of the “riskierallele”. These results suggest that, in general, high-risk patients withischemic heart disease derive the greatest benefit from statin therapy.However, these initial observations should be repeated in other cohortsto further support the predictive value of these specific genotypes.Although it is likely that additional genes beyond the five examplesabove impact the final outcome of an individual's response to statins,these five examples serve to illustrate that it is possible to identifygenes that associate with statin clinical responses that could be usedto predict which patients will benefit from statin treatment and whichwill not.

SNPs

The genomes of all organisms undergo spontaneous mutation in the courseof their continuing evolution, generating variant forms of progenitorgenetic sequences (Gusella, Ann. Rev. Biochem. 55, 831-854 (1986)). Avariant form may confer an evolutionary advantage or disadvantagerelative to a progenitor form or may be neutral. In some instances, avariant form confers an evolutionary advantage to the species and iseventually incorporated into the DNA of many or most members of thespecies and effectively becomes the progenitor form. Additionally, theeffects of a variant form may be both beneficial and detrimental,depending on the circumstances. For example, a heterozygous sickle cellmutation confers resistance to malaria, but a homozygous sickle cellmutation is usually lethal. In many cases, both progenitor and variantforms survive and co-exist in a species population. The coexistence ofmultiple forms of a genetic sequence gives rise to geneticpolymorphisms, including SNPs.

Approximately 90% of all polymorphisms in the human genome are SNPs.SNPs are single base positions in DNA at which different alleles, oralternative nucleotides, exist in a population. The SNP position(interchangeably referred to herein as SNP, SNP site, SNP locus, SNPmarker, or marker) is usually preceded by and followed by highlyconserved sequences of the allele (e.g., sequences that vary in lessthan 1/100 or 1/1000 members of the populations). An individual may behomozygous or heterozygous for an allele at each SNP position. A SNPcan, in some instances, be referred to as a “cSNP” to denote that thenucleotide sequence containing the SNP is an amino acid coding sequence.

A SNP may arise from a substitution of one nucleotide for another at thepolymorphic site. Substitutions can be transitions or transversions. Atransition is the replacement of one purine nucleotide by another purinenucleotide, or one pyrimidine by another pyrimidine. A transversion isthe replacement of a purine by a pyrimidine, or vice versa. A SNP mayalso be a single base insertion or deletion variant referred to as an“indel” (Weber et al., “Human diallelic insertion/deletionpolymorphisms”, Am J Hum Genet 2002 October; 71(4):854-62).

A synonymous codon change, or silent mutation/SNP (terms such as “SNP”,“polymorphism”, “mutation”, “mutant”, “variation”, and “variant” areused herein interchangeably), is one that does not result in a change ofamino acid due to the degeneracy of the genetic code. A substitutionthat changes a codon coding for one amino acid to a codon coding for adifferent amino acid (i.e., a non-synonymous codon change) is referredto as a missense mutation. A nonsense mutation results in a type ofnon-synonymous codon change in which a stop codon is formed, therebyleading to premature termination of a polypeptide chain and a truncatedprotein. A read-through mutation is another type of non-synonymous codonchange that causes the destruction of a stop codon, thereby resulting inan extended polypeptide product. While SNPs can be bi-, tri-, ortetra-allelic, the vast majority of the SNPs are bi-allelic, and arethus often referred to as “bi-allelic markers”, or “di-allelic markers”.

As used herein, references to SNPs and SNP genotypes include individualSNPs and/or haplotypes, which are groups of SNPs that are generallyinherited together. Haplotypes can have stronger correlations withdiseases or other phenotypic effects compared with individual SNPs, andtherefore may provide increased diagnostic accuracy in some cases(Stephens et al. Science 293, 489-493, 20 Jul. 2001).

Causative SNPs are those SNPs that produce alterations in geneexpression or in the expression, structure, and/or function of a geneproduct, and therefore are most predictive of a possible clinicalphenotype. One such class includes SNPs falling within regions of genesencoding a polypeptide product, i.e. cSNPs. These SNPs may result in analteration of the amino acid sequence of the polypeptide product (i.e.,non-synonymous codon changes) and give rise to the expression of adefective or other variant protein. Furthermore, in the case of nonsensemutations, a SNP may lead to premature termination of a polypeptideproduct. Such variant products can result in a pathological condition,e.g., genetic disease. Examples of genes in which a SNP within a codingsequence causes a genetic disease include sickle cell anemia and cysticfibrosis.

Causative SNPs do not necessarily have to occur in coding regions;causative SNPs can occur in, for example, any genetic region that canultimately affect the expression, structure, and/or activity of theprotein encoded by a nucleic acid. Such genetic regions include, forexample, those involved in transcription, such as SNPs in transcriptionfactor binding domains, SNPs in promoter regions, in areas involved intranscript processing, such as SNPs at intron-exon boundaries that maycause defective splicing, or SNPs in mRNA processing signal sequencessuch as polyadenylation signal regions. Some SNPs that are not causativeSNPs nevertheless are in close association with, and therefore segregatewith, a disease-causing sequence. In this situation, the presence of aSNP correlates with the presence of, or predisposition to, or anincreased risk in developing the disease. These SNPs, although notcausative, are nonetheless also useful for diagnostics, diseasepredisposition screening, and other uses.

An association study of a SNP and a specific disorder involvesdetermining the presence or frequency of the SNP allele in biologicalsamples from individuals with the disorder of interest, such as thoseindividuals who respond to statin treatment (“responders”) or thoseindividuals who do not respond to statin treatment (“non-responders”),and comparing the information to that of controls (i.e., individuals whodo not have the disorder; controls may be also referred to as “healthy”or “normal” individuals) who are preferably of similar age and race. Theappropriate selection of patients and controls is important to thesuccess of SNP association studies. Therefore, a pool of individualswith well-characterized phenotypes is extremely desirable.

A SNP may be screened in diseased tissue samples or any biologicalsample obtained from a diseased individual, and compared to controlsamples, and selected for its increased (or decreased) occurrence in aspecific phenotype, such as response or non-response to statin treatmentof cardiovascular disease. Once a statistically significant associationis established between one or more SNP(s) and a pathological condition(or other phenotype) of interest, then the region around the SNP canoptionally be thoroughly screened to identify the causative geneticlocus/sequence(s) (e.g., causative SNP/mutation, gene, regulatoryregion, etc.) that influences the pathological condition or phenotype.Association studies may be conducted within the general population andare not limited to studies performed on related individuals in affectedfamilies (linkage studies).

Clinical trials have shown that patient response to treatment withpharmaceuticals is often heterogeneous. There is a continuing need toimprove pharmaceutical agent design and therapy. In that regard, SNPscan be used to identify patients most suited to therapy with particularpharmaceutical agents such as statins (this is often termed“pharmacogenomics”). Similarly, SNPs can be used to exclude patientsfrom certain treatment due to the patient's increased likelihood ofdeveloping toxic side effects or their likelihood of not responding tothe treatment. Pharmacogenomics can also be used in pharmaceuticalresearch to assist the drug development and selection process. (Linderet al. (1997), Clinical Chemistry, 43, 254; Marshall (1997), NatureBiotechnology, 15, 1249; International Patent Application WO 97/40462,Spectra Biomedical; and Schafer et al. (1998), Nature Biotechnology, 16,3).

SUMMARY OF THE INVENTION

The present invention relates to the identification of novel SNPs,unique combinations of such SNPs, and haplotypes of SNPs that areassociated with cardiovascular disorders and/or drug response,particularly acute cornonary events (e.g., myocardial infarction andstroke) and response to statins for the treatment (including preventivetreatment) of cardiovascular disorders such as acute coronary events.The polymorphisms disclosed herein are directly useful as targets forthe design of diagnostic reagents and the development of therapeuticagents for use in the diagnosis and treatment of cardiovasculardisorders and related pathologies, particularly acute coronary events.

Based on the identification of SNPs associated with cardiovasculardisorders, particularly acute coronary events, and/or response to statintreatment, the present invention also provides methods of detectingthese variants as well as the design and preparation of detectionreagents needed to accomplish this task. The invention specificallyprovides, for example, novel SNPs in genetic sequences involved incardiovascular disorders and/or responsiveness to statin treatment,isolated nucleic acid molecules (including, for example, DNA and RNAmolecules) containing these SNPs, variant proteins encoded by nucleicacid molecules containing such SNPs, antibodies to the encoded variantproteins, computer-based and data storage systems containing the novelSNP information, methods of detecting these SNPs in a test sample,methods of determining the risk of an individual of experiencing a firstor recurring acute coronary event, methods for prognosing the severityor consequences of the acute coronary event, methods of treating anindividual who has an increased risk of experiencing an acute coronaryevent, methods of identifying individuals who have an altered (i.e.,increased or decreased) likelihood of responding to statin treatmentbased on the presence or absence of one or more particular nucleotides(alleles) at one or more SNP sites disclosed herein or the detection ofone or more encoded variant products (e.g., variant mRNA transcripts orvariant proteins), methods of identifying individuals who are more orless likely to respond to a treatment, particularly statin treatment ofa cardiovascular disorder such as an acute coronary event (or more orless likely to experience undesirable side effects from a treatment,etc.), methods of screening for compounds useful in the treatment of adisorder associated with a variant gene/protein, compounds identified bythese methods, methods of treating disorders mediated by a variantgene/protein, methods of using the novel SNPs of the present inventionfor human identification, etc.

Since cardiovascular disorders/diseases share certain similar featuresthat may be due to common genetic factors that are involved in theirunderlying mechanisms, the SNPs identified herein as being particularlyassociated with acute coronary events and/or statin response may be usedas diagnostic/prognostic markers or therapeutic targets for a broadspectrum of cardiovascular diseases such as coronary heart disease(CHD), atherosclerosis, cerebrovascular disease, congestive heartfailure, congenital heart disease, and pathologies and symptomsassociated with various heart diseases (e.g., angina, hypertension), aswell as for predicting responses to a variety of HMG-CoA reductaseinhibitors with lipid-lowering activities (statins), and even drugsother than statins that are used to treat cardiovascular diseases. Inaddition, the SNPs of the present invention are useful for predictingprimary acute coronary events, as well as their reoccurrence.

The present invention further provides methods for selecting orformulating a treatment regimen (e.g., methods for determining whetheror not to administer statin treatment to an individual havingcardiovascular disease, methods for selecting a particular statin-basedtreatment regimen such as dosage and frequency of administration ofstatin, or a particular form/type of statin such as a particularpharmaceutical formulation or compound, methods for administering analternative, non-statin-based treatment to individuals who are predictedto be unlikely to respond positively to statin treatment, etc.), andmethods for determining the likelihood of experiencing toxicity or otherundesirable side effects from statin treatment, etc. The presentinvention also provides methods for selecting individuals to whom astatin or other therapeutic will be administered based on theindividual's genotype, and methods for selecting individuals for aclinical trial of a statin or other therapeutic agent based on thegenotypes of the individuals (e.g., selecting individuals to participatein the trial who are most likely to respond positively from the statintreatment). Furthermore, the SNPs of the invention are useful forpredicting treatment responsiveness at any stage of CHD, including theinitial decision for prescribing treatment before the occurrence of thefirst acute coronary event.

In Tables 1-2, the present invention provides gene information,transcript sequences (SEQ ID NOS:1-517), encoded amino acid sequences(SEQ ID NOS:518-1034), genomic sequences (SEQ ID NOS:13,194-13,514),transcript-based context sequences (SEQ ID NOS:1035-13,193) andgenomic-based context sequences (SEQ ID NOS:13,515-85,090) that containthe SNPs of the present invention, and extensive SNP information thatincludes observed alleles, allele frequencies, populations/ethnic groupsin which alleles have been observed, information about the type of SNPand corresponding functional effect, and, for cSNPs, information aboutthe encoded polypeptide product. The transcript sequences (SEQ IDNOS:1-517), amino acid sequences (SEQ ID NOS:518-1034), genomicsequences (SEQ ID NOS:13,194-13,514), transcript-based SNP contextsequences (SEQ ID NOS: 1035-13,193), and genomic-based SNP contextsequences (SEQ ID NOS:13,515-85,090) are also provided in the sequencelisting.

In a specific embodiment of the present invention, SNPs that occurnaturally in the human genome are provided as isolated nucleic acidmolecules. These SNPs are associated with cardiovascular disorders,particular acute coronary events, and/or response to statin treatment,such that they can have a variety of uses in the diagnosis and/ortreatment of cardiovascular disorders and related pathologies andparticularly in the treatment of cardiovascular disorders with statins.One aspect of the present invention relates to an isolated nucleic acidmolecule comprising a nucleotide sequence in which at least onenucleotide is a SNP disclosed in Tables 3 and/or 4. In an alternativeembodiment, a nucleic acid of the invention is an amplifiedpolynucleotide, which is produced by amplification of a SNP-containingnucleic acid template. In another embodiment, the invention provides fora variant protein which is encoded by a nucleic acid molecule containinga SNP disclosed herein.

In yet another embodiment of the invention, a reagent for detecting aSNP in the context of its naturally-occurring flanking nucleotidesequences (which can be, e.g., either DNA or mRNA) is provided. Inparticular, such a reagent may be in the form of, for example, ahybridization probe or an amplification primer that is useful in thespecific detection of a SNP of interest. In an alternative embodiment, aprotein detection reagent is used to detect a variant protein that isencoded by a nucleic acid molecule containing a SNP disclosed herein. Apreferred embodiment of a protein detection reagent is an antibody or anantigen-reactive antibody fragment.

Various embodiments of the invention also provide kits comprising SNPdetection reagents, and methods for detecting the SNPs disclosed hereinby employing detection reagents. In a specific embodiment, the presentinvention provides for a method of identifying an individual having anincreased or decreased risk of developing a cardiovascular disorder(e.g. experiencing an acute coronary event) by detecting the presence orabsence of one or more SNP alleles disclosed herein. The presentinvention also provides methods for evaluating whether an individual islikely (or unlikely) to respond to statin treatment of cardiovasculardisease by detecting the presence or absence of one or more SNP allelesdisclosed herein.

The nucleic acid molecules of the invention can be inserted in anexpression vector, such as to produce a variant protein in a host cell.Thus, the present invention also provides for a vector comprising aSNP-containing nucleic acid molecule, genetically-engineered host cellscontaining the vector, and methods for expressing a recombinant variantprotein using such host cells. In another specific embodiment, the hostcells, SNP-containing nucleic acid molecules, and/or variant proteinscan be used as targets in a method for screening and identifyingtherapeutic agents or pharmaceutical compounds useful in the treatmentof cardiovascular diseases.

An aspect of this invention is a method for treating cardiovasculardisorders, particular acute coronary events, in a human subject whereinsaid human subject harbors a SNP, gene, transcript, and/or encodedprotein identified in Tables 1-2, which method comprises administeringto said human subject a therapeutically or prophylactically effectiveamount of one or more agents (e.g. statins) counteracting the effects ofthe disorder, such as by inhibiting (or stimulating) the activity of thegene, transcript, and/or encoded protein identified in Tables 1-2.

Another aspect of this invention is a method for identifying an agentuseful in therapeutically or prophylactically treating cardiovasculardisorders, particular acute coronary events, in a human subject whereinsaid human subject harbors a SNP, gene, transcript, and/or encodedprotein identified in Tables 1-2, which method comprises contacting thegene, transcript, or encoded protein with a candidate agent (e.g.,statin) under conditions suitable to allow formation of a bindingcomplex between the gene, transcript, or encoded protein and thecandidate agent (such as a statin) and detecting the formation of thebinding complex, wherein the presence of the complex identifies saidagent.

Another aspect of this invention is a method for treating acardiovascular disorder in a human subject, which method comprises:

(i) determining that said human subject harbors a SNP, gene, transcript,and/or encoded protein identified in Tables 1-2, and

(ii) administering to said subject a therapeutically or prophylacticallyeffective amount of one or more agents (such as a statin) counteractingthe effects of the disease.

Many other uses and advantages of the present invention will be apparentto those skilled in the art upon review of the detailed description ofthe preferred embodiments herein. Solely for clarity of discussion, theinvention is described in the sections below by way of non-limitingexamples.

DESCRIPTION OF THE TEXT (ASCII) FILES SUBMITTED ELECTRONICALLY VIAEFS-WEB

The following text (ASCII) files are submitted electronically viaEFS-Web as part of the instant application:

1) File SEQLIST_1559. txt provides the Sequence Listing. The SequenceListing provides the transcript sequences (SEQ ID NOS:1-517) and proteinsequences (SEQ ID NOS:518-1034) as shown in Table 1, and genomicsequences (SEQ ID NOS:13,194-13,514) as shown in Table 2, for each genethat contains one or more SNPs of the present invention. Also providedin the Sequence Listing are context sequences flanking each SNP,including both transcript-based context sequences as shown in Table 1(SEQ ID NOS:1035-13,193) and genomic-based context sequences as shown inTable 2 (SEQ ID NOS:13,515-85,090). The context sequences generallyprovide 100 bp upstream (5′) and 100 bp downstream (3′) of each SNP,with the SNP in the middle of the context sequence, for a total of 200bp of context sequence surrounding each SNP. File SEQLIST_1559. txt is56,606 KB in size, and was created on Nov. 18, 2004.

2) File TABLE1_1559DIV2.txt provides Table 1. File TABLE1_1559DIV2.txtis 732 KB in size, and was created on Feb. 9, 2010.

3) File TABLE2_1559DIV2.txt provides Table 2. File TABLE2_1559DIV2.txtis 292 KB in size, and was created on Feb. 9, 2010.

4) File TABLE3_1559. txt provides Table 3. File TABLE3_1559. txt is 59KB in size, and was created on Nov. 17, 2004.

5) File TABLE4_1559. txt provides Table 4. File TABLE4_1559. txt is 105KB in size, and was created on Nov. 18, 2004.

These text files are hereby incorporated by reference pursuant to 37 CFR1.77(b)(4).

Furthermore, Table 1 and Table 2 in U.S. application Ser. No.10/995,561, filed Nov. 24, 2004, by Cargill et al., are bothincorporated herein by reference in their entirety.

LENGTHY TABLES The patent application contains a lengthy table section.A copy of the table is available in electronic form from the USPTO website(http://seqdata.uspto.gov/?pageRequest=docDetail&DocID=US20180305762A1).An electronic copy of the table will also be available from the USPTOupon request and payment of the fee set forth in 37 CFR 1.19(b)(3).

Description of Table 1 and Table 2

Table 1 and Table 2 disclose the SNP and associatedgene/transcript/protein information of the present invention. For eachgene, Table 1 and Table 2 each provide a header containinggene/transcript/protein information, followed by a transcript andprotein sequence (in Table 1) or genomic sequence (in Table 2), and thenSNP information regarding each SNP found in that gene/transcript.

NOTE: SNPs may be included in both Table 1 and Table 2; Table 1 presentsthe SNPs relative to their transcript sequences and encoded proteinsequences, whereas Table 2 presents the SNPs relative to their genomicsequences (in some instances Table 2 may also include, after the lastgene sequence, genomic sequences of one or more intergenic regions, aswell as SNP context sequences and other SNP information for any SNPsthat lie within these intergenic regions). SNPs can readily becross-referenced between Tables based on their hCV (or, in someinstances, hDV) identification numbers.

The gene/transcript/protein information includes:

-   -   a gene number (1 through n, where n=the total number of genes in        the Table)    -   a Celera hCG and UID internal identification numbers for the        gene    -   a Celera hCT and UID internal identification numbers for the        transcript (Table 1 only)    -   a public Genbank accession number (e.g., RefSeq NM number) for        the transcript (Table 1 only)    -   a Celera hCP and UID internal identification numbers for the        protein encoded by the hCT transcript (Table 1 only)    -   a public Genbank accession number (e.g., RefSeq NP number) for        the protein (Table 1 only)    -   an art-known gene symbol    -   an art-known gene/protein name    -   Celera genomic axis position (indicating start nucleotide        position-stop nucleotide position)    -   the chromosome number of the chromosome on which the gene is        located    -   an OMIM (Online Mendelian Inheritance in Man; Johns Hopkins        University/NCBI) public reference number for obtaining further        information regarding the medical significance of each gene    -   alternative gene/protein name(s) and/or symbol(s) in the OMIM        entry

NOTE: Due to the presence of alternative splice forms, multipletranscript/protein entries can be provided for a single gene entry inTable 1; i.e., for a single Gene Number, multiple entries may beprovided in series that differ in their transcript/protein informationand sequences.

Following the gene/transcript/protein information is a transcriptsequence and protein sequence (in Table 1), or a genomic sequence (inTable 2), for each gene, as follows:

-   -   transcript sequence (Table 1 only) (corresponding to SEQ ID        NOS:1-517 of the Sequence Listing), with SNPs identified by        their IUB codes (transcript sequences can include 5′ UTR,        protein coding, and 3′ UTR regions). (NOTE: If there are        differences between the nucleotide sequence of the hCT        transcript and the corresponding public transcript sequence        identified by the Genbank accession number, the hCT transcript        sequence (and encoded protein) is provided, unless the public        sequence is a RefSeq transcript sequence identified by an NM        number, in which case the RefSeq NM transcript sequence (and        encoded protein) is provided. However, whether the hCT        transcript or RefSeq NM transcript is used as the transcript        sequence, the disclosed SNPs are represented by their IUB codes        within the transcript.)    -   the encoded protein sequence (Table 1 only) (corresponding to        SEQ ID NOS:518-1034 of the Sequence Listing)    -   the genomic sequence of the gene (Table 2 only), including 6 kb        on each side of the gene boundaries (i.e., 6 kb on the 5′ side        of the gene plus 6 kb on the 3′ side of the gene) (corresponding        to SEQ ID NOS:13,194-13,514 of the Sequence Listing).

After the last gene sequence, Table 2 may include additional genomicsequences of intergenic regions (in such instances, these sequences areidentified as “Intergenic region:” followed by a numericalidentification number), as well as SNP context sequences and other SNPinformation for any SNPs that lie within each intergenic region (andsuch SNPs are identified as “INTERGENIC” for SNP type).

NOTE: The transcript, protein, and transcript-based SNP contextsequences are provided in both Table 1 and in the Sequence Listing. Thegenomic and genomic-based SNP context sequences are provided in bothTable 2 and in the Sequence Listing. SEQ ID NOS are indicated in Table 1for each transcript sequence (SEQ ID NOS:1-517), protein sequence (SEQID NOS:518-1034), and transcript-based SNP context sequence (SEQ IDNOS:1035-13,193), and SEQ ID NOS are indicated in Table 2 for eachgenomic sequence (SEQ ID NOS:13,194-13,514), and genomic-based SNPcontext sequence (SEQ ID NOS:13,515-85,090).

The SNP information includes:

-   -   context sequence (taken from the transcript sequence in Table 1,        and taken from the genomic sequence in Table 2) with the SNP        represented by its IUB code, including 100 bp upstream (5′) of        the SNP position plus 100 bp downstream (3′) of the SNP position        (the transcript-based SNP context sequences in Table 1 are        provided in the Sequence Listing as SEQ ID NOS:1035-13,193; the        genomic-based SNP context sequences in Table 2 are provided in        the Sequence Listing as SEQ ID NOS:13,515-85,090).    -   Celera hCV internal identification number for the SNP (in some        instances, an “hDV” number is given instead of an “hCV” number)    -   SNP position [position of the SNP within the given transcript        sequence (Table 1) or within the given genomic sequence (Table        2)]    -   SNP source (may include any combination of one or more of the        following five codes, depending on which internal sequencing        projects and/or public databases the SNP has been observed in:        “Applera”=SNP observed during the re-sequencing of genes and        regulatory regions of 39 individuals, “Celera”=SNP observed        during shotgun sequencing and assembly of the Celera human        genome sequence, “Celera Diagnostics”=SNP observed during        re-sequencing of nucleic acid samples from individuals who have        cardiovascular disorders (e.g., experienced an acute coronary        event), and/or have undergone statin treatment, “dbSNP”=SNP        observed in the dbSNP public database, “HGBASE”=SNP observed in        the HGBASE public database, “HGMD”=SNP observed in the Human        Gene Mutation Database (HGMD) public database, “HapMap”=SNP        observed in the International HapMap Project public database,        “CSNP”=SNP observed in an internal Applied Biosystems (Foster        City, Calif.) database of coding SNPS (cSNPs)) (NOTE: multiple        “Applera” source entries for a single SNP indicate that the same        SNP was covered by multiple overlapping amplification products        and the re-sequencing results (e.g., observed allele counts)        from each of these amplification products is being provided)    -   Population/allele/allele count information in the format of        [population1(first_allele,countlsecond_allele,count)population2(first_allele,countlsecond_allele,count)        total (first_allele,total countlsecond_allele,total count)]. The        information in this field includes populations/ethnic groups in        which particular SNP alleles have been observed        (“cau”=Caucasian, “his”=Hispanic, “chn”=Chinese, and        “afr”=African-American, “jpn”=Japanese, “ind”=Indian,        “mex”=Mexican, “ain”=“American Indian, “cra”=Celera donor,        “no_pop”=no population information available), identified SNP        alleles, and observed allele counts (within each population        group and total allele counts), where available [“-” in the        allele field represents a deletion allele of an        insertion/deletion (“indel”) polymorphism (in which case the        corresponding insertion allele, which may be comprised of one or        more nucleotides, is indicated in the allele field on the        opposite side of the “I”); “-” in the count field indicates that        allele count information is not available]. For certain SNPs        from the public dbSNP database, population/ethnic information is        indicated as follows (this population information is publicly        available in dbSNP): “HISP1”=human individual DNA (anonymized        samples) from 23 individuals of self-described HISPANIC        heritage; “PAC1”=human individual DNA (anonymized samples) from        24 individuals of self-described PACIFIC RIM heritage; “CAUL        1”=human individual DNA (anonymized samples) from 31 individuals        of self-described CAUCASIAN heritage; “AFR1”=human individual        DNA (anonymized samples) from 24 individuals of self-described        AFRICAN/AFRICAN AMERICAN heritage; “P1”=human individual DNA        (anonymized samples) from 102 individuals of self-described        heritage; “PA130299515”; “SC_12_A”=SANGER 12 DNAs of Asian        origin from Corielle cell repositories, 6 of which are male and        6 female; “SC_12_C”=SANGER 12 DNAs of Caucasian origin from        Corielle cell repositories from the CEPH/UTAH library. Six male        and 6 female; “SC_12_AA”=SANGER 12 DNAs of African-American        origin from Corielle cell repositories 6 of which are male and 6        female; “SC_95_C”=SANGER 95 DNAs of Caucasian origin from        Corielle cell repositories from the CEPH/UTAH library; and        “SC_12_CA”=Caucasians—12 DNAs from Corielle cell repositories        that are from the CEPH/UTAH library. Six male and 6 female.

NOTE: For SNPs of “Applera” SNP source, genes/regulatory regions of 39individuals (20 Caucasians and 19 African Americans) were re-sequencedand, since each SNP position is represented by two chromosomes in eachindividual (with the exception of SNPs on X and Y chromosomes in males,for which each SNP position is represented by a single chromosome), upto 78 chromosomes were genotyped for each SNP position. Thus, the sum ofthe African-American (“afr”) allele counts is up to 38, the sum of theCaucasian allele counts (“cau”) is up to 40, and the total sum of allallele counts is up to 78.

(NOTE: semicolons separate population/allele/count informationcorresponding to each indicated SNP source; i.e., if four SNP sourcesare indicated, such as “Celera”, “dbSNP”, “HGBASE”, and “HGMD”, thenpopulation/allele/count information is provided in four groups which areseparated by semicolons and listed in the same order as the listing ofSNP sources, with each population/allele/count information groupcorresponding to the respective SNP source based on order; thus, in thisexample, the first population/allele/count information group wouldcorrespond to the first listed SNP source (Celera) and the thirdpopulation/allele/count information group separated by semicolons wouldcorrespond to the third listed SNP source (HGBASE); ifpopulation/allele/count information is not available for any particularSNP source, then a pair of semicolons is still inserted as aplace-holder in order to maintain correspondence between the list of

SNP sources and the corresponding listing of population/allele/countinformation)—SNP type (e.g., location within gene/transcript and/orpredicted functional effect) [“MIS-SENSE MUTATION”=SNP causes a changein the encoded amino acid (i.e., a non-synonymous coding SNP); “SILENTMUTATION”=SNP does not cause a change in the encoded amino acid (i.e., asynonymous coding SNP); “STOP CODON MUTATION”=SNP is located in a stopcodon; “NONSENSE MUTATION”=SNP creates or destroys a stop codon; “UTR5”=SNP is located in a 5′ UTR of a transcript; “UTR 3”=SNP is located ina 3′ UTR of a transcript; “PUTATIVE UTR 5”=SNP is located in a putative5′ UTR; “PUTATIVE UTR 3”=SNP is located in a putative 3′ UTR; “DONORSPLICE SITE”=SNP is located in a donor splice site (5′ intron boundary);“ACCEPTOR SPLICE SITE”=SNP is located in an acceptor splice site (3′intron boundary); “CODING REGION”=SNP is located in a protein-codingregion of the transcript; “EXON”=SNP is located in an exon; “INTRON”=SNPis located in an intron; “hmCS”=SNP is located in a human-mouseconserved segment; “TFBS”=SNP is located in a transcription factorbinding site; “UNKNOWN”=SNP type is not defined; “INTERGENIC”=SNP isintergenic, i.e., outside of any gene boundary]

-   -   Protein coding information (Table 1 only), where relevant, in        the format of [protein SEQ ID NO:#, amino acid position, (amino        acid-1, codon1) (amino acid-2, codon2)]. The information in this        field includes SEQ ID NO of the encoded protein sequence,        position of the amino acid residue within the protein identified        by the SEQ ID NO that is encoded by the codon containing the        SNP, amino acids (represented by one-letter amino acid codes)        that are encoded by the alternative SNP alleles (in the case of        stop codons, “X” is used for the one-letter amino acid code),        and alternative codons containing the alternative SNP        nucleotides which encode the amino acid residues (thus, for        example, for missense mutation-type SNPs, at least two different        amino acids and at least two different codons are generally        indicated; for silent mutation-type SNPs, one amino acid and at        least two different codons are generally indicated, etc.). In        instances where the SNP is located outside of a protein-coding        region (e.g., in a UTR region), “None” is indicated following        the protein SEQ ID NO.

Description of Table 3 and Table 4

Tables 3 and 4 provide a list of a subset of SNPs from Table 1 (in thecase of Table 3) or Table 2 (in the case of Table 4) for which the SNPsource falls into one of the following three categories: 1) SNPs forwhich the SNP source is only “Applera” and none other, 2) SNPs for whichthe SNP source is only “Celera Diagnostics” and none other, and 3) SNPsfor which the SNP source is both “Applera” and “Celera Diagnostics” butnone other.

These SNPs have not been observed in any of the public databases (dbSNP,HGBASE, and HGMD), and were also not observed during shotgun sequencingand assembly of the Celera human genome sequence (i.e., “Celera” SNPsource). Tables 3 and 4 provide the hCV identification number (or hDVidentification number for SNPs having “Celera Diagnostics” SNP source)and the SEQ ID NO of the context sequence for each of these SNPs.

Description of Table 5

Table 5 provides sequences (SEQ ID NOS:85,091-85,702) of primers thathave been synthesized and used in the laboratory to carry outallele-specific PCR reactions in order to assay the SNPs disclosed inTables 6-15 during the course of association studies to verify theassociation of these SNPs with cardiovascular disorders (particularlyacute coronary events such as myocardial infarction and stroke) andstatin response.

Table 5 provides the following:

-   -   the column labeled “Marker” provides an hCV identification        number for each SNP site    -   the column labeled “Alleles” designates the two alternative        alleles at the SNP site identified by the hCV identification        number that are targeted by the allele-specific primers (the        allele-specific primers are shown as “Sequence A” and “Sequence        B”) [NOTE: Alleles may be presented in Table 5 based on a        different orientation (i.e., the reverse complement) relative to        how the same alleles are presented in Tables 1-2].    -   the column labeled “Sequence A (allele-specific primer)”        provides an allele-specific primer that is specific for an        allele designated in the “Alleles” column    -   the column labeled “Sequence B (allele-specific primer)”        provides an allele-specific primer that is specific for the        other allele designated in the “Alleles” column    -   the column labeled “Sequence C (common primer)” provides a        common primer that is used in conjunction with each of the        allele-specific primers (the “Sequence A” primer and the        “Sequence B” primer) and which hybridizes at a site away from        the SNP position.

All primer sequences are given in the 5′ to 3′ direction.

Each of the nucleotides designated in the “Alleles” column matches or isthe reverse complement of (depending on the orientation of the primerrelative to the designated allele) the 3′ nucleotide of theallele-specific primer (either “Sequence A” or “Sequence B”) that isspecific for that allele.

Description of Tables 6-15

Tables 6-15 provide results of statistical analyses for SNPs disclosedin Tables 1-4 (SNPs can be cross-referenced between tables based ontheir hCV identification numbers), and the association of these SNPswith various cardiovascular disease clinical endpoints or drug responsetraits. The statistical results shown in Tables 6-15 provide support forthe association of these SNPs with cardiovascular disorders,particularly acute coronary events such as myocardial infarction andstroke, and/or the association of these SNPs with response to statintreatment, such as statin treatment administered as a preventivetreatment for acute coronary events. For example, the statisticalresults provided in Tables 6-15 show that the association of these SNPswith acute coronary events and/or response to statin treatment issupported by p-values <0.05 in an allelic association test.

Table 6 presents statistical associations of SNPs with various trialendpoints. Table 7 presents statistical associations of SNPs withclinical variables such as lab tests at base line and at the end of atrial. Table 8 presents statistical associations of SNPs withcardiovascular endpoints prevention (SNPs predictive of response tostatins as a preventive treatment). Table 9 shows the association ofSNPs with adverse coronary events such as RMI and stroke in CAREsamples. This association of certain SNPs with adverse coronary eventscould also be replicated by comparing associations in samples betweeninitial analysis and replication (see example section). Table 10 showsassociation of SNPs predictive of statin response with cardiovascularevents prevention under statin treatment, justified by stepwise logisticregression analysis with an adjustment for conventional risk factorssuch as age, sex, smoking status, baseline glucose levels, body massindex (BMI), history of hypertension, etc. (this adjustment supportsindependence of the SNP association from conventional risk factors). Thestatistical results provided in Table 11 demonstrate association of aSNP in the CD6 gene that is predictive of statin response in theprevention of RMI, justified as a significant difference in riskassociated with the SNP between placebo and Statin treated strata(Breslow Day p-values <0.05). Table 11 presents the results observed insamples taken from both the CARE and WOSCOP studies. In both studies theindividuals homozygous for the minor allele were statistically differentfrom heterozygous and major allele homozygous individuals in thepravastatin treated group vs. the placebo treated group. Table 12 showsthe association of a SNP in the FCAR gene that is predictive of MI riskand response to statin treatment. Individuals who participated in boththe CARE and WOSCOPS studies, who did not receive pravastatin treatmentand who were heterozygous or homozygous for the major allele had asignificantly higher risk of having an MI vs. individuals who werehomozygous for the minor allele. However, individuals in the CARE studywho were heterozygous or homozygous for the FCAR major allele were alsostatistically significantly protected by pravastatin treatment againstan adverse coronary event relative to the individuals homozygous for theminor allele.

NOTE: SNPs can be cross-referenced between all tables herein based onthe hCV identification number of each SNP. However, eleven of the SNPsthat are included in the tables may possess two different hCVidentification numbers, as follows:

-   -   hCV15871020 is equivalent to hCV22273027    -   hCV15962586 is equivalent to hCV22274323    -   hCV16192174 is equivalent to hCV22271999    -   hCV22273204 is equivalent to hCV16179443    -   hCV25617571 is equivalent to hCV15943347    -   hCV25637308 is equivalent to hCV27501445    -   hCV25637309 is equivalent to hCV27469009    -   hCV25640926 is equivalent to hCV9485713    -   hCV7499900 is equivalent to hCV25620145    -   hCV16172571 is equivalent to hCV25474627    -   hCV16273460 is equivalent to hCV26165616

TABLE 6 column heading Definition Public Locus Link HUGO approved genesymbol for the gene that contains the tested SNP Marker Internal hCVidentification number for the tested SNP Stratum Subpopulation used foranalysis Phenotype Disease endpoints (definitions of entries in thiscolumn are provided below) Overall* Result of the Overall Score Test(chi-square test) Chi-square Test: for the logistic regression model inwhich the statistic/ qualitative phenotype is a function of SNP p-valuegenotype (based on placebo patients only) SNP effect** Result of thechi-square test of the SNP effect Chi-square Test: (based on thelogistic regression model for placebo statistic/ patients only) p-valuePlacebo Patients “n” is the number of placebo patients with no raren/total(%) alleles genotype for investigated phenotype. The 0 RareAlleles “total” is the total number of placebo patients with thisgenotype, and “%” is the percentage of placebo patients with thisgenotype. Placebo Patients “n” is the number of placebo patients withone rare n/total(%) allele genotype for investigated phenotype. The 1Rare Allele “total” is the total number of placebo patients with thisgenotype, and “%” is the percentage of placebo patients with thisgenotype. Placebo Patients “n” is the number of placebo patients withtwo rare n/total(%) alleles genotype for investigated phenotype. The 2Rare Alleles “total” is the total number of placebo patients with thisgenotype, and “%” is the percentage of placebo patients with thisgenotype. Odd Ratio (95% Cl) “Odds ratio” indicates the odds of havingthis 2 Rare Alleles vs. phenotype given that genotype contains two rare0 Rare Alleles alleles of a SNP versus the odds of having this phenotypegiven a genotype containing no rare alleles. “95% Cl” is the 95%confidence interval. Odd Ratio (95% Cl) “Odds ratio” indicates the oddsof having this 1 Rare Alleles vs. phenotype given that genotype containsone rare 0 Rare Alleles allele versus the odds of having this phenotypegiven a genotype containing no rare alleles. “95% Cl” is the 95%confidence interval Significance Level “Significance Level” indicatesthe summary of the result of the “Overall Score Test (chi-square test)”for the logistic regression model and the result of the “chi-square testof the SNP effect”. If both p- values are less than 0.05, “<0.05” isindicated. If both p-values are less than 0.005, “<0.005” is indicated.

TABLE 7 column heading Definition Public Locus Link HUGO approved genesymbol for the gene that contains the tested SNP Marker Internal hCVidentification number for the tested SNP Stratum Subpopulation used foranalysis Phenotype Clinical quantitative variables - lab test results at(at Baseline) baseline or change from baseline discharge (definitions ofentries in this column are provided below) Overall* Results of theOverall F-Test for the analysis of F-Test: variance model in which thequantitative phenotype statistic/ is a function of SNP genotype (basedon placebo p-value patients only) SNP effect** Results of the F-test ofthe SNP effect (based on the F-Test: analysis of variance model forplacebo patients only) statistic/ p-value Placebo Patients “n” is thenumber of placebo patients with a tested Mean (se)# (N) SNP genotype(zero rare alleles) and presented 0 Rare Alleles phenotype. “Mean” isthe least squares estimate of the mean phenotype result for placebopatients with this genotype. “se” is the least squares estimate of thestandard error of the mean phenotype for placebo patients with 0 rareallele genotype Placebo Patients “n” is the number of placebo patientswith a tested Mean (se)# (N) SNP genotype (one rare allele) andpresented 1 Rare Allele phenotype. Mean is the least squares estimate ofthe mean phenotype result for placebo patients with this genotype. se isthe least squares estimate of the standard error of the mean phenotypefor placebo patients 1 rare allele genotype Placebo Patients “n” is thenumber of placebo patients with a tested Mean (se)# (N) SNP genotype(one rare allele) and presented 2 Rare Alleles phenotype. Mean is theleast squares estimate of the mean phenotype result for placebo patientswith this genotype. se is the least squares estimate of the standarderror of the mean phenotype for placebo patients 2 rare alleles genotypeSignificance “Significance Level” indicates the summary of the Levelresult of the “Overall F-Test” for the analysis of variance model andthe result of the “F-test of the SNP effect”. If both p-values are lessthan 0.05, “<0.05” is indicated. If both p-values are less than 0.005,“<0.005” is indicated.

TABLE 8 column Definition heading Public Locus Link HUGO approved genesymbol for the gene that contains the tested SNP Marker Internal hCVidentification number for the tested SNP Stratum Subpopulation used foranalysis Phenotype Disease endpoints (definitions of entries in thiscolumn are provided below) Overall* Results of the Overall Score Test(chi-square test) Chi-square Test: for the regression model in which thequalitative statistic/ phenotype is a function of the SNP genotype,p-value treatment group, and the interaction between SNP genotype andtreatment group Interaction Effect** Results of the chi-square test ofthe interaction Chi-square Test: between SNP genotype and treatmentgroup (based statistic/ on the logistic regression model). p-value 0Rare Alleles Results for patients under pravastatin treatment. n/total(%) “n” is the number of pravastatin patients with no Prava rare allelegenotype and the investigated phenotype. The “total” is the total numberof pravastatin patients with this genotype. “%” is the percentage ofpravastatin patients with this genotype who had the investigatedphenotype. 0 Rare Alleles Results for patients under placebo. “n” is then/total (%) number of placebo patients with no rare allele Placebogenotype and investigated phenotype. “Total” is the total number ofplacebo patients with the genotype.“%” is the percentage of placebopatients with no rare allele genotype and the investigated phenotype. 1Rare Allele Results for patients under pravastatin treatment. n/total(%) “n” is the number of patients under pravastatin with Prava one rareallele genotype and the investigated phenotype. The “total” is the totalnumber of pravastatin patients with the genotype. “%” is the percentageof pravastatin patients with one rare allele genotype and theinvestigated phenotype. 1 Rare Allele Results for patients on placebo.“n” is the number n/total (%) of placebo patients with one rare allelegenotype Placebo and the investigated phenotype. The “total” is thetotal number of pravastatin patients with the genotype. “%” is thepercentage of pravastatin patients with one rare allele genotype and theinvestigated phenotype. 2 Rare Alleles Results for patients underpravastatin treatment. n/total (%) “n” is the number of patients underpravastatin with Prava two rare allele genotype and the investigatedphenotype. The “total” is the total number of pravastatin patients withthe genotype. “%” is the percentage of pravastatin patients with tworare allele genotypes and the investigated phenotype 2 Rare AllelesResults for patients on placebo. “n” is the number n/total (%) ofplacebo patients with two rare allele genotype Placebo and theinvestigated phenotype . The “total” is the total number of pravastatinpatients with the genotype. “%” is the percentage of pravastatinpatients with two rare allele genotypes and the investigated phenotypePrava vs Placebo Odds ratio and its 95% confidence interval for OddsRatio patients with no rare allele genotype, the odd ratios (95% Cl) ofhaving the event given pravastatin use versus the 0 Rare Alleles odds ofhaving the event on placebo Prava vs Placebo Odds ratio and its 95%confidence interval for Odds Ratio patients with one rare allelegenotype, the odd (95% Cl) ratios of having the event given pravastatinuse 1 Rare Allele versus the odds of having the event on placebo Pravavs Placebo Odds ratio and its 95% confidence interval for Odds Ratiopatients with two rare alleles genotype, the odd (95% Cl) ratio ofhaving the event given pravastatin use 2 Rare Alleles versus the odds ofhaving the event on placebo Significance Level “Significance Level”indicates the summary of the result of the “Overall Score Test(chi-square test)” for the regression model and the result of the “chi-square test of the interaction“. If both p-values are less than 0.05,“<0.05” is indicated. If both p- values are less than 0.005, “<0.005” isindicated.

TABLE 9 column heading Definition Endpoint Endpoint measured in studyPublic Locus Link HUGO approved gene symbol for the gene that containsthe tested SNP Marker Internal hCV identification number for the SNPthat is tested Genotype/mode Effect seen in major homozygous (“Maj.Hom”), minor homozygous (“Min Hom”) or heterozygous (Het”)/recessive(“Rec”) or dominant (“Dom”) Strata Indicates whether the analysis of thedataset has been stratified by genotypes, such as major homozygote (“MajHom”), minor homozygote (“Min Hom”), and heterozygote (“Het”)Confounders Variables that change the marker risk estimates by ≥5% Prisk est. Significance of risk estimated by Wald Test RR Relative risk95% Cl 95% confidence interval for relative risk case Number of patients(with the corresponding genotype or mode) developed recurrent MI orStroke during 5 years follow up Case AF (%) The allele frequency ofpatients (with the corresponding genotype or mode) that developedrecurrent MI during 6 years follow up Control Number of patients (withthe corresponding genotype or mode) that had MI Control AF (%) Theallele frequency of patients (with the corresponding genotype or mode)that had MI Analysis 1 Statistics are based on initial analysis (seeexamples). Analysis 2 Statistics are based on replication analysis (seeexamples)

TABLE 10 See Table footnotes and Examples section

TABLE 11 See Table footnotes and Examples section

TABLE 12 See Table footnotes and Examples section

TABLE 13 See Table footnotes and Examples section

TABLE 14 See Table footnotes and Examples section

TABLE 15 See Table footnotes and Examples section

Definition of Entries in the “Phenotype” Column of Table 6:

Phenotype Definite Nonfatal MI Fatal CHD/Definite Nonfatal MI CARE MI:Q-Wave MI MI (Fatal/Nonfatal) Fatal Coronary Heart Disease TotalMortality Cardiovascular Mortality Fatal Atherosclerotic CardiovascularDisease History of Diabetes Stroke Percutaneous Transluminal CoronaryAngioplasty Hosp. for Cardiovascular Disease Fatal/NonfatalCerebrovascular Disease Hosp. for Unstable Angina Total CardiovascularDisease Events Any Report of Stroke Prior to or During CARE Any Reportof Stroke During CARE 1st Stroke Occurred During CARE Fatal/Nonfatal MI(def & prob) History of Congestive Heart Failure (AE) Nonfatal MI(Probable/Definite) Nonfatal MI (def & prob) Fatal/NonfatalAtherosclerotic CV Disease Coronary Artery Bypass Graft Coronary ArteryBypass or Revascularization Congestive Heart Failure Hosp. forPeripheral Arterial Disease History of Coronary Artery Bypass Graft CAREMI: Non Q-Wave MI Fatal MI History of Percutaneous Transluminal CoronaryAngioplasty Catheterization Total Coronary Heart Disease Events Historyof Angina Pectoris More Than 1 Prior MI Family History of CV DiseaseHistory of Hypertension History of Stroke

Definition of Entries in the “Phenotype (at Baseline)” Column of Table7:

Phenotype (at Baseline) Change from Baseline in Urinary Glucose (atLOCF) Change from Baseline in Urinary Glucose (at LOCF) Baseline HDLBaseline Lymphocytes, Absolute (k/cumm) Baseline HDL

Definition of Entries in the “Phenotype” Column of Table 8:

Phenotype Catheterization Nonfatal MI (Probable/Definite) Nonfatal MI(def & prob) Family History of CV Disease MI (Fatal/Nonfatal) DefiniteNonfatal MI Fatal/Nonfatal MI (def & prob) Fatal Coronary Heart DiseaseTotal Mortality Total Coronary Heart Disease Events CardiovascularMortality Fatal Atherosclerotic Cardiovascular Disease Fatal/NonfatalAtherosclerotic CV Disease Hosp. for Cardiovascular Disease TotalCardiovascular Disease Events History of Angina Pectoris FatalCHD/Definite Nonfatal MI Coronary Artery Bypass or RevascularizationCoronary Artery Bypass Graft Hospitalization for Unstable AnginaPercutaneous Transluminal Coronary Angioplasty Fatal/NonfatalCerebrovascular Disease Stroke

DESCRIPTION OF THE FIGURE

FIG. 1 provides a diagrammatic representation of a computer-baseddiscovery system containing the SNP information of the present inventionin computer readable form.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides SNPs associated with cardiovasculardisorders, particularly acute coronary events such as myocardialinfarction and stroke (including recurrent acute coronary events such asrecurrent myocardial infarction), and SNPs that are associated with anindividual's responsiveness to therapeutic agents, particularlylipid-lowering compounds such as statins, that are used for thetreatment (including preventive treatment) of cardiovascular disorders,particularly treatment of acute coronary events. The present inventionfurther provides nucleic acid molecules containing these SNPs, methodsand reagents for the detection of the SNPs disclosed herein, uses ofthese SNPs for the development of detection reagents, and assays or kitsthat utilize such reagents. The acute coronary event-associated SNPs andstatin response-associated SNPs disclosed herein are useful fordiagnosing, screening for, and evaluating an individual's increased ordecreased risk of developing cardiovascular disease as well as theirresponsiveness to drug treatment. Furthermore, such SNPs and theirencoded products are useful targets for the development of therapeuticagents.

A large number of SNPs have been identified from re-sequencing DNA from39 individuals, and they are indicated as “Applera” SNP source in Tables1-2. Their allele frequencies observed in each of the Caucasian andAfrican-American ethnic groups are provided. Additional SNPs includedherein were previously identified during shotgun sequencing and assemblyof the human genome, and they are indicated as “Celera” SNP source inTables 1-2. Furthermore, the information provided in Table 1-2,particularly the allele frequency information obtained from 39individuals and the identification of the precise position of each SNPwithin each gene/transcript, allows haplotypes (i.e., groups of SNPsthat are co-inherited) to be readily inferred. The present inventionencompasses SNP haplotypes, as well as individual SNPs.

Thus, the present invention provides individual SNPs associated withcardiovascular disorders, particularly acute coronary events, and SNPsassociated with responsiveness to statin for the treatment ofcardiovascular diseases, as well as combinations of SNPs and haplotypesin genetic regions associated with cardiovascular disorders and/orstatin response, polymorphic/variant transcript sequences (SEQ IDNOS:1-517) and genomic sequences (SEQ ID NOS:13,194-13,514) containingSNPs, encoded amino acid sequences (SEQ ID NOS: 518-1034), and bothtranscript-based SNP context sequences (SEQ ID NOS: 1035-13,193) andgenomic-based SNP context sequences (SEQ ID NOS:13,515-85,090)(transcript sequences, protein sequences, and transcript-based SNPcontext sequences are provided in Table 1 and the Sequence Listing;genomic sequences and genomic-based SNP context sequences are providedin Table 2 and the Sequence Listing), methods of detecting thesepolymorphisms in a test sample, methods of determining the risk of anindividual of having or developing a cardiovascular disorder such as anacute coronary event, methods of determining response to statintreatment of cardiovascular disease, methods of screening for compoundsuseful for treating cardiovascular disease, compounds identified bythese screening methods, methods of using the disclosed SNPs to select atreatment strategy, methods of treating a disorder associated with avariant gene/protein (i.e., therapeutic methods), and methods of usingthe SNPs of the present invention for human identification.

Since cardiovascular disorders/diseases share certain similar featuresthat may be due to common genetic factors that are involved in theirunderlying mechanisms, the SNPs identified herein as being particularlyassociated with acute coronary events and/or statin response may be usedas diagnostic/prognostic markers or therapeutic targets for a broadspectrum of cardiovascular diseases such as coronary heart disease(CHD), atherosclerosis, cerebrovascular disease, congestive heartfailure, congenital heart disease, and pathologies and symptomsassociated with various heart diseases (e.g., angina, hypertension), aswell as for predicting responses to drugs other than statins that areused to treat cardiovascular diseases.

The present invention further provides methods for selecting orformulating a treatment regimen (e.g., methods for determining whetheror not to administer statin treatment to an individual havingcardiovascular disease, methods for selecting a particular statin-basedtreatment regimen such as dosage and frequency of administration ofstatin, or a particular form/type of statin such as a particularpharmaceutical formulation or compound, methods for administering analternative, non-statin-based treatment to individuals who are predictedto be unlikely to respond positively to statin treatment, etc.), andmethods for determining the likelihood of experiencing toxicity or otherundesirable side effects from statin treatment, etc. The presentinvention also provides methods for selecting individuals to whom astatin or other therapeutic will be administered based on theindividual's genotype, and methods for selecting individuals for aclinical trial of a statin or other therapeutic agent based on thegenotypes of the individuals (e.g., selecting individuals to participatein the trial who are most likely to respond positively from the statintreatment).

The present invention provides novel SNPs associated with cardiovasculardisorders and/or response to statin treatment, as well as SNPs that werepreviously known in the art, but were not previously known to beassociated with cardiovascular disorders and/or statin response.Accordingly, the present invention provides novel compositions andmethods based on the novel SNPs disclosed herein, and also providesnovel methods of using the known, but previously unassociated, SNPs inmethods relating to evaluating an individual's likelihood of having ordeveloping a cardiovascular disorder, predicting the likelihood of anindividual experiencing a reoccurrence of a cardiovascular disorder(e.g., experiencing recurrent myocardial infarctions), prognosing theseverity of a cardiovascular disorder in an individual, or prognosing anindividual's recovery from a cardiovascular disorder, and methodsrelating to evaluating an individual's likelihood of responding tostatin treatment for cardiovascular disease. In Tables 1-2, known SNPsare identified based on the public database in which they have beenobserved, which is indicated as one or more of the following SNP types:“dbSNP”=SNP observed in dbSNP, “HGBASE”=SNP observed in HGBASE, and“HGMD”=SNP observed in the Human Gene Mutation Database (HGMD). NovelSNPs for which the SNP source is only “Applera” and none other, i.e.,those that have not been observed in any public databases and which werealso not observed during shotgun sequencing and assembly of the Celerahuman genome sequence (i.e., “Celera” SNP source), are indicated inTables 3-4.

Particular SNP alleles of the present invention can be associated witheither an increased risk of having a cardiovascular disorder (e.g.,experiencing an acute coronary event) or of responding to statintreatment of cardiovascular disease, or a decreased likelihood of havinga cardiovascular disorder or of responding to statin treatment ofcardiovascular disease. Thus, whereas certain SNPs (or their encodedproducts) can be assayed to determine whether an individual possesses aSNP allele that is indicative of an increased likelihood of experiencinga coronary event or of responding to statin treatment, other SNPs (ortheir encoded products) can be assayed to determine whether anindividual possesses a SNP allele that is indicative of a decreasedlikelihood of experiencing a coronary event or of responding to statintreatment. Similarly, particular SNP alleles of the present inventioncan be associated with either an increased or decreased likelihood ofhaving a reoccurrence of a cardiovascular disorder, of fully recoveringfrom a cardiovascular disorder, of experiencing toxic effects from aparticular treatment or therapeutic compound, etc. The term “altered”may be used herein to encompass either of these two possibilities (e.g.,an increased or a decreased risk/likelihood). SNP alleles that areassociated with a decreased risk of having or developing acardiovascular disorder such as myocardial infarction may be referred toas “protective” alleles, and SNP alleles that are associated with anincreased risk of having or developing a cardiovascular disorder may bereferred to as “susceptibility” alleles, “risk” alleles, or “riskfactors”.

Those skilled in the art will readily recognize that nucleic acidmolecules may be double-stranded molecules and that reference to aparticular site on one strand refers, as well, to the corresponding siteon a complementary strand. In defining a SNP position, SNP allele, ornucleotide sequence, reference to an adenine, a thymine (uridine), acytosine, or a guanine at a particular site on one strand of a nucleicacid molecule also defines the thymine (uridine), adenine, guanine, orcytosine (respectively) at the corresponding site on a complementarystrand of the nucleic acid molecule. Thus, reference may be made toeither strand in order to refer to a particular SNP position, SNPallele, or nucleotide sequence. Probes and primers, may be designed tohybridize to either strand and SNP genotyping methods disclosed hereinmay generally target either strand. Throughout the specification, inidentifying a SNP position, reference is generally made to theprotein-encoding strand, only for the purpose of convenience.

References to variant peptides, polypeptides, or proteins of the presentinvention include peptides, polypeptides, proteins, or fragmentsthereof, that contain at least one amino acid residue that differs fromthe corresponding amino acid sequence of the art-knownpeptide/polypeptide/protein (the art-known protein may beinterchangeably referred to as the “wild-type”, “reference”, or “normal”protein). Such variant peptides/polypeptides/proteins can result from acodon change caused by a nonsynonymous nucleotide substitution at aprotein-coding SNP position (i.e., a missense mutation) disclosed by thepresent invention. Variant peptides/polypeptides/proteins of the presentinvention can also result from a nonsense mutation, i.e. a SNP thatcreates a premature stop codon, a SNP that generates a read-throughmutation by abolishing a stop codon, or due to any SNP disclosed by thepresent invention that otherwise alters the structure,function/activity, or expression of a protein, such as a SNP in aregulatory region (e.g. a promoter or enhancer) or a SNP that leads toalternative or defective splicing, such as a SNP in an intron or a SNPat an exon/intron boundary. As used herein, the terms “polypeptide”,“peptide”, and “protein” are used interchangeably.

Isolated Nucleic Acid Molecules

And SNP Detection Reagents & Kits

Tables 1 and 2 provide a variety of information about each SNP of thepresent invention that is associated with cardiovascular disorders(e.g., acute coronary events such as myocardial infarction and stroke)and/or responsiveness to statin treatment, including the transcriptsequences (SEQ ID NOS:1-517), genomic sequences (SEQ IDNOS:13,194-13,514), and protein sequences (SEQ ID NOS:518-1034) of theencoded gene products (with the SNPs indicated by IUB codes in thenucleic acid sequences). In addition, Tables 1 and 2 include SNP contextsequences, which generally include 100 nucleotide upstream (5′) plus 100nucleotides downstream (3′) of each SNP position (SEQ ID NOS:1035-13,193correspond to transcript-based SNP context sequences disclosed in Table1, and SEQ ID NOS:13,515-85,090 correspond to genomic-based contextsequences disclosed in Table 2), the alternative nucleotides (alleles)at each SNP position, and additional information about the variant whererelevant, such as SNP type (coding, missense, splice site, UTR, etc.),human populations in which the SNP was observed, observed allelefrequencies, information about the encoded protein, etc.

Isolated Nucleic Acid Molecules

The present invention provides isolated nucleic acid molecules thatcontain one or more SNPs disclosed Table 1 and/or Table 2. Preferredisolated nucleic acid molecules contain one or more SNPs identified inTable 3 and/or Table 4. Isolated nucleic acid molecules containing oneor more SNPs disclosed in at least one of Tables 1-4 may beinterchangeably referred to throughout the present text as“SNP-containing nucleic acid molecules”. Isolated nucleic acid moleculesmay optionally encode a full-length variant protein or fragment thereof.The isolated nucleic acid molecules of the present invention alsoinclude probes and primers (which are described in greater detail belowin the section entitled “SNP Detection Reagents”), which may be used forassaying the disclosed SNPs, and isolated full-length genes,transcripts, cDNA molecules, and fragments thereof, which may be usedfor such purposes as expressing an encoded protein.

As used herein, an “isolated nucleic acid molecule” generally is onethat contains a SNP of the present invention or one that hybridizes tosuch molecule such as a nucleic acid with a complementary sequence, andis separated from most other nucleic acids present in the natural sourceof the nucleic acid molecule. Moreover, an “isolated” nucleic acidmolecule, such as a cDNA molecule containing a SNP of the presentinvention, can be substantially free of other cellular material, orculture medium when produced by recombinant techniques, or chemicalprecursors or other chemicals when chemically synthesized. A nucleicacid molecule can be fused to other coding or regulatory sequences andstill be considered “isolated”. Nucleic acid molecules present innon-human transgenic animals, which do not naturally occur in theanimal, are also considered “isolated”. For example, recombinant DNAmolecules contained in a vector are considered “isolated”. Furtherexamples of “isolated” DNA molecules include recombinant DNA moleculesmaintained in heterologous host cells, and purified (partially orsubstantially) DNA molecules in solution. Isolated RNA molecules includein vivo or in vitro RNA transcripts of the isolated SNP-containing DNAmolecules of the present invention. Isolated nucleic acid moleculesaccording to the present invention further include such moleculesproduced synthetically.

Generally, an isolated SNP-containing nucleic acid molecule comprisesone or more SNP positions disclosed by the present invention withflanking nucleotide sequences on either side of the SNP positions. Aflanking sequence can include nucleotide residues that are naturallyassociated with the SNP site and/or heterologous nucleotide sequences.Preferably the flanking sequence is up to about 500, 300, 100, 60, 50,30, 25, 20, 15, 10, 8, or 4 nucleotides (or any other length in-between)on either side of a SNP position, or as long as the full-length gene orentire protein-coding sequence (or any portion thereof such as an exon),especially if the SNP-containing nucleic acid molecule is to be used toproduce a protein or protein fragment.

For full-length genes and entire protein-coding sequences, a SNPflanking sequence can be, for example, up to about 5 KB, 4 KB, 3 KB, 2KB, 1 KB on either side of the SNP. Furthermore, in such instances, theisolated nucleic acid molecule comprises exonic sequences (includingprotein-coding and/or non-coding exonic sequences), but may also includeintronic sequences. Thus, any protein coding sequence may be eithercontiguous or separated by introns. The important point is that thenucleic acid is isolated from remote and unimportant flanking sequencesand is of appropriate length such that it can be subjected to thespecific manipulations or uses described herein such as recombinantprotein expression, preparation of probes and primers for assaying theSNP position, and other uses specific to the SNP-containing nucleic acidsequences.

An isolated SNP-containing nucleic acid molecule can comprise, forexample, a full-length gene or transcript, such as a gene isolated fromgenomic DNA (e.g., by cloning or PCR amplification), a cDNA molecule, oran mRNA transcript molecule. Polymorphic transcript sequences areprovided in Table 1 and in the Sequence Listing (SEQ ID NOS: 1-517), andpolymorphic genomic sequences are provided in Table 2 and in theSequence Listing (SEQ ID NOS:13,194-13,514). Furthermore, fragments ofsuch full-length genes and transcripts that contain one or more SNPsdisclosed herein are also encompassed by the present invention, and suchfragments may be used, for example, to express any part of a protein,such as a particular functional domain or an antigenic epitope.

Thus, the present invention also encompasses fragments of the nucleicacid sequences provided in Tables 1-2 (transcript sequences are providedin Table 1 as SEQ ID NOS:1-517, genomic sequences are provided in Table2 as SEQ ID NOS:13,194-13,514, transcript-based SNP context sequencesare provided in Table 1 as SEQ ID NO:1035-13,193, and genomic-based SNPcontext sequences are provided in Table 2 as SEQ ID NO:13,515-85,090)and their complements. A fragment typically comprises a contiguousnucleotide sequence at least about 8 or more nucleotides, morepreferably at least about 12 or more nucleotides, and even morepreferably at least about 16 or more nucleotides. Further, a fragmentcould comprise at least about 18, 20, 22, 25, 30, 40, 50, 60, 80, 100,150, 200, 250 or 500 (or any other number in-between) nucleotides inlength. The length of the fragment will be based on its intended use.For example, the fragment can encode epitope-bearing regions of avariant peptide or regions of a variant peptide that differ from thenormal/wild-type protein, or can be useful as a polynucleotide probe orprimer. Such fragments can be isolated using the nucleotide sequencesprovided in Table 1 and/or Table 2 for the synthesis of a polynucleotideprobe. A labeled probe can then be used, for example, to screen a cDNAlibrary, genomic DNA library, or mRNA to isolate nucleic acidcorresponding to the coding region. Further, primers can be used inamplification reactions, such as for purposes of assaying one or moreSNPs sites or for cloning specific regions of a gene.

An isolated nucleic acid molecule of the present invention furtherencompasses a SNP-containing polynucleotide that is the product of anyone of a variety of nucleic acid amplification methods, which are usedto increase the copy numbers of a polynucleotide of interest in anucleic acid sample. Such amplification methods are well known in theart, and they include but are not limited to, polymerase chain reaction(PCR) (U.S. Pat. Nos. 4,683,195; and 4,683,202; PCR Technology:Principles and Applications for DNA Amplification, ed. H. A. Erlich,Freeman Press, NY, NY, 1992), ligase chain reaction (LCR) (Wu andWallace, Genomics 4:560, 1989; Landegren et al., Science 241:1077,1988), strand displacement amplification (SDA) (U.S. Pat. Nos.5,270,184; and 5,422,252), transcription-mediated amplification (TMA)(U.S. Pat. No. 5,399,491), linked linear amplification (LLA) (U.S. Pat.No. 6,027,923), and the like, and isothermal amplification methods suchas nucleic acid sequence based amplification (NASBA), and self-sustainedsequence replication (Guatelli et al., Proc. Natl. Acad. Sci. USA 87:1874, 1990). Based on such methodologies, a person skilled in the artcan readily design primers in any suitable regions 5′ and 3′ to a SNPdisclosed herein. Such primers may be used to amplify DNA of any lengthso long that it contains the SNP of interest in its sequence.

As used herein, an “amplified polynucleotide” of the invention is aSNP-containing nucleic acid molecule whose amount has been increased atleast two fold by any nucleic acid amplification method performed invitro as compared to its starting amount in a test sample. In otherpreferred embodiments, an amplified polynucleotide is the result of atleast ten fold, fifty fold, one hundred fold, one thousand fold, or eventen thousand fold increase as compared to its starting amount in a testsample. In a typical PCR amplification, a polynucleotide of interest isoften amplified at least fifty thousand fold in amount over theunamplified genomic DNA, but the precise amount of amplification neededfor an assay depends on the sensitivity of the subsequent detectionmethod used.

Generally, an amplified polynucleotide is at least about 16 nucleotidesin length. More typically, an amplified polynucleotide is at least about20 nucleotides in length. In a preferred embodiment of the invention, anamplified polynucleotide is at least about 30 nucleotides in length. Ina more preferred embodiment of the invention, an amplifiedpolynucleotide is at least about 32, 40, 45, 50, or 60 nucleotides inlength. In yet another preferred embodiment of the invention, anamplified polynucleotide is at least about 100, 200, 300, 400, or 500nucleotides in length. While the total length of an amplifiedpolynucleotide of the invention can be as long as an exon, an intron orthe entire gene where the SNP of interest resides, an amplified productis typically up to about 1,000 nucleotides in length (although certainamplification methods may generate amplified products greater than 1000nucleotides in length). More preferably, an amplified polynucleotide isnot greater than about 600-700 nucleotides in length. It is understoodthat irrespective of the length of an amplified polynucleotide, a SNP ofinterest may be located anywhere along its sequence.

In a specific embodiment of the invention, the amplified product is atleast about 201 nucleotides in length, comprises one of thetranscript-based context sequences or the genomic-based contextsequences shown in Tables 1-2. Such a product may have additionalsequences on its 5′ end or 3′ end or both. In another embodiment, theamplified product is about 101 nucleotides in length, and it contains aSNP disclosed herein. Preferably, the SNP is located at the middle ofthe amplified product (e.g., at position 101 in an amplified productthat is 201 nucleotides in length, or at position 51 in an amplifiedproduct that is 101 nucleotides in length), or within 1, 2, 3, 4, 5, 6,7, 8, 9, 10, 12, 15, or 20 nucleotides from the middle of the amplifiedproduct (however, as indicated above, the SNP of interest may be locatedanywhere along the length of the amplified product).

The present invention provides isolated nucleic acid molecules thatcomprise, consist of, or consist essentially of one or morepolynucleotide sequences that contain one or more SNPs disclosed herein,complements thereof, and SNP-containing fragments thereof.

Accordingly, the present invention provides nucleic acid molecules thatconsist of any of the nucleotide sequences shown in Table 1 and/or Table2 (transcript sequences are provided in Table 1 as SEQ ID NOS:1-517,genomic sequences are provided in Table 2 as SEQ ID NOS:13,194-13,514,transcript-based SNP context sequences are provided in Table 1 as SEQ IDNO:1035-13,193, and genomic-based SNP context sequences are provided inTable 2 as SEQ ID NO:13,515-85,090), or any nucleic acid molecule thatencodes any of the variant proteins provided in Table 1 (SEQ IDNOS:518-1034). A nucleic acid molecule consists of a nucleotide sequencewhen the nucleotide sequence is the complete nucleotide sequence of thenucleic acid molecule.

The present invention further provides nucleic acid molecules thatconsist essentially of any of the nucleotide sequences shown in Table 1and/or Table 2 (transcript sequences are provided in Table 1 as SEQ IDNOS:1-517, genomic sequences are provided in Table 2 as SEQ IDNOS:13,194-13,514, transcript-based SNP context sequences are providedin Table 1 as SEQ ID NO:1035-13,193, and genomic-based SNP contextsequences are provided in Table 2 as SEQ ID NO:13,515-85,090), or anynucleic acid molecule that encodes any of the variant proteins providedin Table 1 (SEQ ID NOS:518-1034). A nucleic acid molecule consistsessentially of a nucleotide sequence when such a nucleotide sequence ispresent with only a few additional nucleotide residues in the finalnucleic acid molecule.

The present invention further provides nucleic acid molecules thatcomprise any of the nucleotide sequences shown in Table 1 and/or Table 2or a SNP-containing fragment thereof (transcript sequences are providedin Table 1 as SEQ ID NOS:1-517, genomic sequences are provided in Table2 as SEQ ID NOS:13,194-13,514, transcript-based SNP context sequencesare provided in Table 1 as SEQ ID NO:1035-13,193, and genomic-based SNPcontext sequences are provided in Table 2 as SEQ ID NO:13,515-85,090),or any nucleic acid molecule that encodes any of the variant proteinsprovided in Table 1 (SEQ ID NOS:518-1034). A nucleic acid moleculecomprises a nucleotide sequence when the nucleotide sequence is at leastpart of the final nucleotide sequence of the nucleic acid molecule. Insuch a fashion, the nucleic acid molecule can be only the nucleotidesequence or have additional nucleotide residues, such as residues thatare naturally associated with it or heterologous nucleotide sequences.Such a nucleic acid molecule can have one to a few additionalnucleotides or can comprise many more additional nucleotides. A briefdescription of how various types of these nucleic acid molecules can bereadily made and isolated is provided below, and such techniques arewell known to those of ordinary skill in the art (Sambrook and Russell,2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press,NY).

The isolated nucleic acid molecules can encode mature proteins plusadditional amino or carboxyl-terminal amino acids or both, or aminoacids interior to the mature peptide (when the mature form has more thanone peptide chain, for instance). Such sequences may play a role inprocessing of a protein from precursor to a mature form, facilitateprotein trafficking, prolong or shorten protein half-life, or facilitatemanipulation of a protein for assay or production. As generally is thecase in situ, the additional amino acids may be processed away from themature protein by cellular enzymes.

Thus, the isolated nucleic acid molecules include, but are not limitedto, nucleic acid molecules having a sequence encoding a peptide alone, asequence encoding a mature peptide and additional coding sequences suchas a leader or secretory sequence (e.g., a pre-pro or pro-proteinsequence), a sequence encoding a mature peptide with or withoutadditional coding sequences, plus additional non-coding sequences, forexample introns and non-coding 5′ and 3′ sequences such as transcribedbut untranslated sequences that play a role in, for example,transcription, mRNA processing (including splicing and polyadenylationsignals), ribosome binding, and/or stability of mRNA. In addition, thenucleic acid molecules may be fused to heterologous marker sequencesencoding, for example, a peptide that facilitates purification.

Isolated nucleic acid molecules can be in the form of RNA, such as mRNA,or in the form DNA, including cDNA and genomic DNA, which may beobtained, for example, by molecular cloning or produced by chemicalsynthetic techniques or by a combination thereof (Sambrook and Russell,2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press,NY). Furthermore, isolated nucleic acid molecules, particularly SNPdetection reagents such as probes and primers, can also be partially orcompletely in the form of one or more types of nucleic acid analogs,such as peptide nucleic acid (PNA) (U.S. Pat. Nos. 5,539,082; 5,527,675;5,623,049; 5,714,331). The nucleic acid, especially DNA, can bedouble-stranded or single-stranded. Single-stranded nucleic acid can bethe coding strand (sense strand) or the complementary non-coding strand(anti-sense strand). DNA, RNA, or PNA segments can be assembled, forexample, from fragments of the human genome (in the case of DNA or RNA)or single nucleotides, short oligonucleotide linkers, or from a seriesof oligonucleotides, to provide a synthetic nucleic acid molecule.Nucleic acid molecules can be readily synthesized using the sequencesprovided herein as a reference; oligonucleotide and PNA oligomersynthesis techniques are well known in the art (see, e.g., Corey,“Peptide nucleic acids: expanding the scope of nucleic acidrecognition”, Trends Biotechnol. 1997 June; 15(6):224-9, and Hyrup etal., “Peptide nucleic acids (PNA): synthesis, properties and potentialapplications”, Bioorg Med Chem. 1996 January; 4(1):5-23). Furthermore,large-scale automated oligonucleotide/PNA synthesis (including synthesison an array or bead surface or other solid support) can readily beaccomplished using commercially available nucleic acid synthesizers,such as the Applied Biosystems (Foster City, Calif.) 3900High-Throughput DNA Synthesizer or Expedite 8909 Nucleic Acid SynthesisSystem, and the sequence information provided herein.

The present invention encompasses nucleic acid analogs that containmodified, synthetic, or non-naturally occurring nucleotides orstructural elements or other alternative/modified nucleic acidchemistries known in the art. Such nucleic acid analogs are useful, forexample, as detection reagents (e.g., primers/probes) for detecting oneor more SNPs identified in Table 1 and/or Table 2. Furthermore,kits/systems (such as beads, arrays, etc.) that include these analogsare also encompassed by the present invention. For example, PNAoligomers that are based on the polymorphic sequences of the presentinvention are specifically contemplated. PNA oligomers are analogs ofDNA in which the phosphate backbone is replaced with a peptide-likebackbone (Lagriffoul et al., Bioorganic & Medicinal Chemistry Letters,4: 1081-1082 (1994), Petersen et al., Bioorganic & Medicinal ChemistryLetters, 6: 793-796 (1996), Kumar et al., Organic Letters 3(9):1269-1272 (2001), WO96/04000). PNA hybridizes to complementary RNA orDNA with higher affinity and specificity than conventionaloligonucleotides and oligonucleotide analogs. The properties of PNAenable novel molecular biology and biochemistry applicationsunachievable with traditional oligonucleotides and peptides.

Additional examples of nucleic acid modifications that improve thebinding properties and/or stability of a nucleic acid include the use ofbase analogs such as inosine, intercalators (U.S. Pat. No. 4,835,263)and the minor groove binders (U.S. Pat. No. 5,801,115). Thus, referencesherein to nucleic acid molecules, SNP-containing nucleic acid molecules,SNP detection reagents (e.g., probes and primers),oligonucleotides/polynucleotides include PNA oligomers and other nucleicacid analogs. Other examples of nucleic acid analogs andalternative/modified nucleic acid chemistries known in the art aredescribed in Current Protocols in Nucleic Acid Chemistry, John Wiley &Sons, N.Y. (2002).

The present invention further provides nucleic acid molecules thatencode fragments of the variant polypeptides disclosed herein as well asnucleic acid molecules that encode obvious variants of such variantpolypeptides. Such nucleic acid molecules may be naturally occurring,such as paralogs (different locus) and orthologs (different organism),or may be constructed by recombinant DNA methods or by chemicalsynthesis. Non-naturally occurring variants may be made by mutagenesistechniques, including those applied to nucleic acid molecules, cells, ororganisms. Accordingly, the variants can contain nucleotidesubstitutions, deletions, inversions and insertions (in addition to theSNPs disclosed in Tables 1-2). Variation can occur in either or both thecoding and non-coding regions. The variations can produce conservativeand/or non-conservative amino acid substitutions.

Further variants of the nucleic acid molecules disclosed in Tables 1-2,such as naturally occurring allelic variants (as well as orthologs andparalogs) and synthetic variants produced by mutagenesis techniques, canbe identified and/or produced using methods well known in the art. Suchfurther variants can comprise a nucleotide sequence that shares at least70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%sequence identity with a nucleic acid sequence disclosed in Table 1and/or Table 2 (or a fragment thereof) and that includes a novel SNPallele disclosed in Table 1 and/or Table 2. Further, variants cancomprise a nucleotide sequence that encodes a polypeptide that shares atleast 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or99% sequence identity with a polypeptide sequence disclosed in Table 1(or a fragment thereof) and that includes a novel SNP allele disclosedin Table 1 and/or Table 2. Thus, an aspect of the present invention thatis specifically contemplated are isolated nucleic acid molecules thathave a certain degree of sequence variation compared with the sequencesshown in Tables 1-2, but that contain a novel SNP allele disclosedherein. In other words, as long as an isolated nucleic acid moleculecontains a novel SNP allele disclosed herein, other portions of thenucleic acid molecule that flank the novel SNP allele can vary to somedegree from the specific transcript, genomic, and context sequencesshown in Tables 1-2, and can encode a polypeptide that varies to somedegree from the specific polypeptide sequences shown in Table 1.

To determine the percent identity of two amino acid sequences or twonucleotide sequences of two molecules that share sequence homology, thesequences are aligned for optimal comparison purposes (e.g., gaps can beintroduced in one or both of a first and a second amino acid or nucleicacid sequence for optimal alignment and non-homologous sequences can bedisregarded for comparison purposes). In a preferred embodiment, atleast 30%, 40%, 50%, 60%, 70%, 80%, or 90% or more of the length of areference sequence is aligned for comparison purposes. The amino acidresidues or nucleotides at corresponding amino acid positions ornucleotide positions are then compared. When a position in the firstsequence is occupied by the same amino acid residue or nucleotide as thecorresponding position in the second sequence, then the molecules areidentical at that position (as used herein, amino acid or nucleic acid“identity” is equivalent to amino acid or nucleic acid “homology”). Thepercent identity between the two sequences is a function of the numberof identical positions shared by the sequences, taking into account thenumber of gaps, and the length of each gap, which need to be introducedfor optimal alignment of the two sequences.

The comparison of sequences and determination of percent identitybetween two sequences can be accomplished using a mathematicalalgorithm. (Computational Molecular Biology, Lesk, A. M., ed., OxfordUniversity Press, New York, 1988; Biocomputing: Informatics and GenomeProjects, Smith, D. W., ed., Academic Press, New York, 1993; ComputerAnalysis of Sequence Data, Part 1, Griffin, A. M., and Griffin, H. G.,eds., Humana Press, New Jersey, 1994; Sequence Analysis in MolecularBiology, von Heinje, G., Academic Press, 1987; and Sequence AnalysisPrimer, Gribskov, M. and Devereux, J., eds., M Stockton Press, New York,1991). In a preferred embodiment, the percent identity between two aminoacid sequences is determined using the Needleman and Wunsch algorithm(J. Mol. Biol. (48):444-453 (1970)) which has been incorporated into theGAP program in the GCG software package, using either a Blossom 62matrix or a PAM250 matrix, and a gap weight of 16, 14, 12, 10, 8, 6, or4 and a length weight of 1, 2, 3, 4, 5, or 6.

In yet another preferred embodiment, the percent identity between twonucleotide sequences is determined using the GAP program in the GCGsoftware package (Devereux, J., et al., Nucleic Acids Res. 12(1):387(1984)), using a NWSgapdna.CMP matrix and a gap weight of 40, 50, 60,70, or 80 and a length weight of 1, 2, 3, 4, 5, or 6. In anotherembodiment, the percent identity between two amino acid or nucleotidesequences is determined using the algorithm of E. Myers and W. Miller(CABIOS, 4:11-17 (1989)) which has been incorporated into the ALIGNprogram (version 2.0), using a PAM120 weight residue table, a gap lengthpenalty of 12, and a gap penalty of 4.

The nucleotide and amino acid sequences of the present invention canfurther be used as a “query sequence” to perform a search againstsequence databases to, for example, identify other family members orrelated sequences. Such searches can be performed using the NBLAST andXBLAST programs (version 2.0) of Altschul, et al. (J. Mol. Biol.215:403-10 (1990)). BLAST nucleotide searches can be performed with theNBLAST program, score=100, wordlength=12 to obtain nucleotide sequenceshomologous to the nucleic acid molecules of the invention. BLAST proteinsearches can be performed with the XBLAST program, score=50,wordlength=3 to obtain amino acid sequences homologous to the proteinsof the invention. To obtain gapped alignments for comparison purposes,Gapped BLAST can be utilized as described in Altschul et al. (NucleicAcids Res. 25(17):3389-3402 (1997)). When utilizing BLAST and gappedBLAST programs, the default parameters of the respective programs (e.g.,XBLAST and NBLAST) can be used. In addition to BLAST, examples of othersearch and sequence comparison programs used in the art include, but arenot limited to, FASTA (Pearson, Methods Mol. Biol. 25, 365-389 (1994))and KERR (Dufresne et al., Nat Biotechnol 2002 December;20(12):1269-71). For further information regarding bioinformaticstechniques, see Current Protocols in Bioinformatics, John Wiley & Sons,Inc., N.Y.

The present invention further provides non-coding fragments of thenucleic acid molecules disclosed in Table 1 and/or Table 2. Preferrednon-coding fragments include, but are not limited to, promotersequences, enhancer sequences, intronic sequences, 5′ untranslatedregions (UTRs), 3′ untranslated regions, gene modulating sequences andgene termination sequences. Such fragments are useful, for example, incontrolling heterologous gene expression and in developing screens toidentify gene-modulating agents.

SNP Detection Reagents

In a specific aspect of the present invention, the SNPs disclosed inTable 1 and/or Table 2, and their associated transcript sequences(provided in Table 1 as SEQ ID NOS:1-517), genomic sequences (providedin Table 2 as SEQ ID NOS:13,194-13,514), and context sequences(transcript-based context sequences are provided in Table 1 as SEQ IDNOS:1035-13,193; genomic-based context sequences are provided in Table 2as SEQ ID NOS:13,515-85,090), can be used for the design of SNPdetection reagents. As used herein, a “SNP detection reagent” is areagent that specifically detects a specific target SNP positiondisclosed herein, and that is preferably specific for a particularnucleotide (allele) of the target SNP position (i.e., the detectionreagent preferably can differentiate between different alternativenucleotides at a target SNP position, thereby allowing the identity ofthe nucleotide present at the target SNP position to be determined).Typically, such detection reagent hybridizes to a target SNP-containingnucleic acid molecule by complementary base-pairing in a sequencespecific manner, and discriminates the target variant sequence fromother nucleic acid sequences such as an art-known form in a test sample.An example of a detection reagent is a probe that hybridizes to a targetnucleic acid containing one or more of the SNPs provided in Table 1and/or Table 2. In a preferred embodiment, such a probe candifferentiate between nucleic acids having a particular nucleotide(allele) at a target SNP position from other nucleic acids that have adifferent nucleotide at the same target SNP position. In addition, adetection reagent may hybridize to a specific region 5′ and/or 3′ to aSNP position, particularly a region corresponding to the contextsequences provided in Table 1 and/or Table 2 (transcript-based contextsequences are provided in Table 1 as SEQ ID NOS:1035-13,193;genomic-based context sequences are provided in Table 2 as SEQ IDNOS:13,515-85,090). Another example of a detection reagent is a primerwhich acts as an initiation point of nucleotide extension along acomplementary strand of a target polynucleotide. The SNP sequenceinformation provided herein is also useful for designing primers, e.g.allele-specific primers, to amplify (e.g., using PCR) any SNP of thepresent invention.

In one preferred embodiment of the invention, a SNP detection reagent isan isolated or synthetic DNA or RNA polynucleotide probe or primer orPNA oligomer, or a combination of DNA, RNA and/or PNA, that hybridizesto a segment of a target nucleic acid molecule containing a SNPidentified in Table 1 and/or Table 2. A detection reagent in the form ofa polynucleotide may optionally contain modified base analogs,intercalators or minor groove binders. Multiple detection reagents suchas probes may be, for example, affixed to a solid support (e.g., arraysor beads) or supplied in solution (e.g., probe/primer sets for enzymaticreactions such as PCR, RT-PCR, TaqMan assays, or primer-extensionreactions) to form a SNP detection kit.

A probe or primer typically is a substantially purified oligonucleotideor PNA oligomer. Such oligonucleotide typically comprises a region ofcomplementary nucleotide sequence that hybridizes under stringentconditions to at least about 8, 10, 12, 16, 18, 20, 22, 25, 30, 40, 50,55, 60, 65, 70, 80, 90, 100, 120 (or any other number in-between) ormore consecutive nucleotides in a target nucleic acid molecule.Depending on the particular assay, the consecutive nucleotides caneither include the target SNP position, or be a specific region in closeenough proximity 5′ and/or 3′ to the SNP position to carry out thedesired assay.

Other preferred primer and probe sequences can readily be determinedusing the transcript sequences (SEQ ID NOS:1-517), genomic sequences(SEQ ID NOS:13,194-13,514), and SNP context sequences (transcript-basedcontext sequences are provided in Table 1 as SEQ ID NOS:1035-13,193;genomic-based context sequences are provided in Table 2 as SEQ IDNOS:13,515-85,090) disclosed in the Sequence Listing and in Tables 1-2.It will be apparent to one of skill in the art that such primers andprobes are directly useful as reagents for genotyping the SNPs of thepresent invention, and can be incorporated into any kit/system format.

In order to produce a probe or primer specific for a targetSNP-containing sequence, the gene/transcript and/or context sequencesurrounding the SNP of interest is typically examined using a computeralgorithm which starts at the 5′ or at the 3′ end of the nucleotidesequence. Typical algorithms will then identify oligomers of definedlength that are unique to the gene/SNP context sequence, have a GCcontent within a range suitable for hybridization, lack predictedsecondary structure that may interfere with hybridization, and/orpossess other desired characteristics or that lack other undesiredcharacteristics.

A primer or probe of the present invention is typically at least about 8nucleotides in length. In one embodiment of the invention, a primer or aprobe is at least about 10 nucleotides in length. In a preferredembodiment, a primer or a probe is at least about 12 nucleotides inlength. In a more preferred embodiment, a primer or probe is at leastabout 16, 17, 18, 19, 20, 21, 22, 23, 24 or 25 nucleotides in length.While the maximal length of a probe can be as long as the targetsequence to be detected, depending on the type of assay in which it isemployed, it is typically less than about 50, 60, 65, or 70 nucleotidesin length. In the case of a primer, it is typically less than about 30nucleotides in length. In a specific preferred embodiment of theinvention, a primer or a probe is within the length of about 18 andabout 28 nucleotides. However, in other embodiments, such as nucleicacid arrays and other embodiments in which probes are affixed to asubstrate, the probes can be longer, such as on the order of 30-70, 75,80, 90, 100, or more nucleotides in length (see the section belowentitled “SNP Detection Kits and Systems”).

For analyzing SNPs, it may be appropriate to use oligonucleotidesspecific for alternative SNP alleles. Such oligonucleotides which detectsingle nucleotide variations in target sequences may be referred to bysuch terms as “allele-specific oligonucleotides”, “allele-specificprobes”, or “allele-specific primers”. The design and use ofallele-specific probes for analyzing polymorphisms is described in,e.g., Mutation Detection A Practical Approach, ed. Cotton et al. OxfordUniversity Press, 1998; Saiki et al., Nature 324, 163-166 (1986);Dattagupta, EP235,726; and Saiki, WO 89/11548.

While the design of each allele-specific primer or probe depends onvariables such as the precise composition of the nucleotide sequencesflanking a SNP position in a target nucleic acid molecule, and thelength of the primer or probe, another factor in the use of primers andprobes is the stringency of the condition under which the hybridizationbetween the probe or primer and the target sequence is performed. Higherstringency conditions utilize buffers with lower ionic strength and/or ahigher reaction temperature, and tend to require a more perfect matchbetween probe/primer and a target sequence in order to form a stableduplex. If the stringency is too high, however, hybridization may notoccur at all. In contrast, lower stringency conditions utilize bufferswith higher ionic strength and/or a lower reaction temperature, andpermit the formation of stable duplexes with more mismatched basesbetween a probe/primer and a target sequence. By way of example and notlimitation, exemplary conditions for high stringency hybridizationconditions using an allele-specific probe are as follows:Prehybridization with a solution containing 5× standard saline phosphateEDTA (SSPE), 0.5% NaDodSO₄ (SDS) at 55° C., and incubating probe withtarget nucleic acid molecules in the same solution at the sametemperature, followed by washing with a solution containing 2×SSPE, and0.1% SDS at 55° C. or room temperature.

Moderate stringency hybridization conditions may be used forallele-specific primer extension reactions with a solution containing,e.g., about 50 mM KCl at about 46° C. Alternatively, the reaction may becarried out at an elevated temperature such as 60° C. In anotherembodiment, a moderately stringent hybridization condition suitable foroligonucleotide ligation assay (OLA) reactions wherein two probes areligated if they are completely complementary to the target sequence mayutilize a solution of about 100 mM KCl at a temperature of 46° C.

In a hybridization-based assay, allele-specific probes can be designedthat hybridize to a segment of target DNA from one individual but do nothybridize to the corresponding segment from another individual due tothe presence of different polymorphic forms (e.g., alternative SNPalleles/nucleotides) in the respective DNA segments from the twoindividuals. Hybridization conditions should be sufficiently stringentthat there is a significant detectable difference in hybridizationintensity between alleles, and preferably an essentially binaryresponse, whereby a probe hybridizes to only one of the alleles orsignificantly more strongly to one allele. While a probe may be designedto hybridize to a target sequence that contains a SNP site such that theSNP site aligns anywhere along the sequence of the probe, the probe ispreferably designed to hybridize to a segment of the target sequencesuch that the SNP site aligns with a central position of the probe(e.g., a position within the probe that is at least three nucleotidesfrom either end of the probe). This design of probe generally achievesgood discrimination in hybridization between different allelic forms.

In another embodiment, a probe or primer may be designed to hybridize toa segment of target DNA such that the SNP aligns with either the 5′ mostend or the 3′ most end of the probe or primer. In a specific preferredembodiment that is particularly suitable for use in a oligonucleotideligation assay (U.S. Pat. No. 4,988,617), the 3′ most nucleotide of theprobe aligns with the SNP position in the target sequence.

Oligonucleotide probes and primers may be prepared by methods well knownin the art. Chemical synthetic methods include, but are limited to, thephosphotriester method described by Narang et al., 1979, Methods inEnzymology 68:90; the phosphodiester method described by Brown et al.,1979, Methods in Enzymology 68:109, the diethylphosphoamidate methoddescribed by Beaucage et al., 1981, Tetrahedron Letters 22:1859; and thesolid support method described in U.S. Pat. No. 4,458,066.

Allele-specific probes are often used in pairs (or, less commonly, insets of 3 or 4, such as if a SNP position is known to have 3 or 4alleles, respectively, or to assay both strands of a nucleic acidmolecule for a target SNP allele), and such pairs may be identicalexcept for a one nucleotide mismatch that represents the allelicvariants at the SNP position. Commonly, one member of a pair perfectlymatches a reference form of a target sequence that has a more common SNPallele (i.e., the allele that is more frequent in the target population)and the other member of the pair perfectly matches a form of the targetsequence that has a less common SNP allele (i.e., the allele that israrer in the target population). In the case of an array, multiple pairsof probes can be immobilized on the same support for simultaneousanalysis of multiple different polymorphisms.

In one type of PCR-based assay, an allele-specific primer hybridizes toa region on a target nucleic acid molecule that overlaps a SNP positionand only primes amplification of an allelic form to which the primerexhibits perfect complementarity (Gibbs, 1989, Nucleic Acid Res. 172427-2448). Typically, the primer's 3′-most nucleotide is aligned withand complementary to the SNP position of the target nucleic acidmolecule. This primer is used in conjunction with a second primer thathybridizes at a distal site. Amplification proceeds from the twoprimers, producing a detectable product that indicates which allelicform is present in the test sample. A control is usually performed witha second pair of primers, one of which shows a single base mismatch atthe polymorphic site and the other of which exhibits perfectcomplementarity to a distal site. The single-base mismatch preventsamplification or substantially reduces amplification efficiency, so thateither no detectable product is formed or it is formed in lower amountsor at a slower pace. The method generally works most effectively whenthe mismatch is at the 3′-most position of the oligonucleotide (i.e.,the 3′-most position of the oligonucleotide aligns with the target SNPposition) because this position is most destabilizing to elongation fromthe primer (see, e.g., WO 93/22456). This PCR-based assay can beutilized as part of the TaqMan assay, described below.

In a specific embodiment of the invention, a primer of the inventioncontains a sequence substantially complementary to a segment of a targetSNP-containing nucleic acid molecule except that the primer has amismatched nucleotide in one of the three nucleotide positions at the3′-most end of the primer, such that the mismatched nucleotide does notbase pair with a particular allele at the SNP site. In a preferredembodiment, the mismatched nucleotide in the primer is the second fromthe last nucleotide at the 3′-most position of the primer. In a morepreferred embodiment, the mismatched nucleotide in the primer is thelast nucleotide at the 3′-most position of the primer.

In another embodiment of the invention, a SNP detection reagent of theinvention is labeled with a fluorogenic reporter dye that emits adetectable signal. While the preferred reporter dye is a fluorescentdye, any reporter dye that can be attached to a detection reagent suchas an oligonucleotide probe or primer is suitable for use in theinvention. Such dyes include, but are not limited to, Acridine, AMCA,BODIPY, Cascade Blue, Cy2, Cy3, Cy5, Cy7, Dabcyl, Edans, Eosin,Erythrosin, Fluorescein, 6-Fam, Tet, Joe, Hex, Oregon Green, Rhodamine,Rhodol Green, Tamra, Rox, and Texas Red.

In yet another embodiment of the invention, the detection reagent may befurther labeled with a quencher dye such as Tamra, especially when thereagent is used as a self-quenching probe such as a TaqMan (U.S. Pat.Nos. 5,210,015 and 5,538,848) or Molecular Beacon probe (U.S. Pat. Nos.5,118,801 and 5,312,728), or other stemless or linear beacon probe(Livak et al., 1995, PCR Method Appl. 4:357-362; Tyagi et al., 1996,Nature Biotechnology 14: 303-308; Nazarenko et al., 1997, Nucl. AcidsRes. 25:2516-2521; U.S. Pat. Nos. 5,866,336 and 6,117,635).

The detection reagents of the invention may also contain other labels,including but not limited to, biotin for streptavidin binding, haptenfor antibody binding, and oligonucleotide for binding to anothercomplementary oligonucleotide such as pairs of zipcodes.

The present invention also contemplates reagents that do not contain (orthat are complementary to) a SNP nucleotide identified herein but thatare used to assay one or more SNPs disclosed herein. For example,primers that flank, but do not hybridize directly to a target SNPposition provided herein are useful in primer extension reactions inwhich the primers hybridize to a region adjacent to the target SNPposition (i.e., within one or more nucleotides from the target SNPsite). During the primer extension reaction, a primer is typically notable to extend past a target SNP site if a particular nucleotide(allele) is present at that target SNP site, and the primer extensionproduct can be detected in order to determine which SNP allele ispresent at the target SNP site. For example, particular ddNTPs aretypically used in the primer extension reaction to terminate primerextension once a ddNTP is incorporated into the extension product (aprimer extension product which includes a ddNTP at the 3′-most end ofthe primer extension product, and in which the ddNTP is a nucleotide ofa SNP disclosed herein, is a composition that is specificallycontemplated by the present invention). Thus, reagents that bind to anucleic acid molecule in a region adjacent to a SNP site and that areused for assaying the SNP site, even though the bound sequences do notnecessarily include the SNP site itself, are also contemplated by thepresent invention.

SNP Detection Kits and Systems

A person skilled in the art will recognize that, based on the SNP andassociated sequence information disclosed herein, detection reagents canbe developed and used to assay any SNP of the present inventionindividually or in combination, and such detection reagents can bereadily incorporated into one of the established kit or system formatswhich are well known in the art. The terms “kits” and “systems”, as usedherein in the context of SNP detection reagents, are intended to referto such things as combinations of multiple SNP detection reagents, orone or more SNP detection reagents in combination with one or more othertypes of elements or components (e.g., other types of biochemicalreagents, containers, packages such as packaging intended for commercialsale, substrates to which SNP detection reagents are attached,electronic hardware components, etc.). Accordingly, the presentinvention further provides SNP detection kits and systems, including butnot limited to, packaged probe and primer sets (e.g., TaqManprobe/primer sets), arrays/microarrays of nucleic acid molecules, andbeads that contain one or more probes, primers, or other detectionreagents for detecting one or more SNPs of the present invention. Thekits/systems can optionally include various electronic hardwarecomponents; for example, arrays (“DNA chips”) and microfluidic systems(“lab-on-a-chip” systems) provided by various manufacturers typicallycomprise hardware components. Other kits/systems (e.g., probe/primersets) may not include electronic hardware components, but may becomprised of, for example, one or more SNP detection reagents (alongwith, optionally, other biochemical reagents) packaged in one or morecontainers.

In some embodiments, a SNP detection kit typically contains one or moredetection reagents and other components (e.g., a buffer, enzymes such asDNA polymerases or ligases, chain extension nucleotides such asdeoxynucleotide triphosphates, and in the case of Sanger-type DNAsequencing reactions, chain terminating nucleotides, positive controlsequences, negative control sequences, and the like) necessary to carryout an assay or reaction, such as amplification and/or detection of aSNP-containing nucleic acid molecule. A kit may further contain meansfor determining the amount of a target nucleic acid, and means forcomparing the amount with a standard, and can comprise instructions forusing the kit to detect the SNP-containing nucleic acid molecule ofinterest. In one embodiment of the present invention, kits are providedwhich contain the necessary reagents to carry out one or more assays todetect one or more SNPs disclosed herein. In a preferred embodiment ofthe present invention, SNP detection kits/systems are in the form ofnucleic acid arrays, or compartmentalized kits, includingmicrofluidic/lab-on-a-chip systems.

SNP detection kits/systems may contain, for example, one or more probes,or pairs of probes, that hybridize to a nucleic acid molecule at or neareach target SNP position. Multiple pairs of allele-specific probes maybe included in the kit/system to simultaneously assay large numbers ofSNPs, at least one of which is a SNP of the present invention. In somekits/systems, the allele-specific probes are immobilized to a substratesuch as an array or bead. For example, the same substrate can compriseallele-specific probes for detecting at least 1; 10; 100; 1000; 10,000;100,000 (or any other number in-between) or substantially all of theSNPs shown in Table 1 and/or Table 2.

The terms “arrays”, “microarrays”, and “DNA chips” are used hereininterchangeably to refer to an array of distinct polynucleotides affixedto a substrate, such as glass, plastic, paper, nylon or other type ofmembrane, filter, chip, or any other suitable solid support. Thepolynucleotides can be synthesized directly on the substrate, orsynthesized separate from the substrate and then affixed to thesubstrate. In one embodiment, the microarray is prepared and usedaccording to the methods described in U.S. Pat. No. 5,837,832, Chee etal., PCT application WO95/11995 (Chee et al.), Lockhart, D. J. et al.(1996; Nat. Biotech. 14: 1675-1680) and Schena, M. et al. (1996; Proc.Natl. Acad. Sci. 93: 10614-10619), all of which are incorporated hereinin their entirety by reference. In other embodiments, such arrays areproduced by the methods described by Brown et al., U.S. Pat. No.5,807,522.

Nucleic acid arrays are reviewed in the following references: Zammatteoet al., “New chips for molecular biology and diagnostics”, BiotechnolAnnu Rev. 2002; 8:85-101; Sosnowski et al., “Active microelectronicarray system for DNA hybridization, genotyping and pharmacogenomicapplications”, Psychiatr Genet. 2002 December; 12(4):181-92; Heller,“DNA microarray technology: devices, systems, and applications”, AnnuRev Biomed Eng. 2002; 4:129-53. Epub 2002 Mar. 22; Kolchinsky et al.,“Analysis of SNPs and other genomic variations using gel-based chips”,Hum Mutat. 2002 April; 19(4):343-60; and McGall et al., “High-densitygenechip oligonucleotide probe arrays”, Adv Biochem Eng Biotechnol.2002; 77:21-42.

Any number of probes, such as allele-specific probes, may be implementedin an array, and each probe or pair of probes can hybridize to adifferent SNP position. In the case of polynucleotide probes, they canbe synthesized at designated areas (or synthesized separately and thenaffixed to designated areas) on a substrate using a light-directedchemical process. Each DNA chip can contain, for example, thousands tomillions of individual synthetic polynucleotide probes arranged in agrid-like pattern and miniaturized (e.g., to the size of a dime).Preferably, probes are attached to a solid support in an ordered,addressable array.

A microarray can be composed of a large number of unique,single-stranded polynucleotides, usually either synthetic antisensepolynucleotides or fragments of cDNAs, fixed to a solid support. Typicalpolynucleotides are preferably about 6-60 nucleotides in length, morepreferably about 15-30 nucleotides in length, and most preferably about18-25 nucleotides in length. For certain types of microarrays or otherdetection kits/systems, it may be preferable to use oligonucleotidesthat are only about 7-20 nucleotides in length. In other types ofarrays, such as arrays used in conjunction with chemiluminescentdetection technology, preferred probe lengths can be, for example, about15-80 nucleotides in length, preferably about 50-70 nucleotides inlength, more preferably about 55-65 nucleotides in length, and mostpreferably about 60 nucleotides in length. The microarray or detectionkit can contain polynucleotides that cover the known 5′ or 3′ sequenceof a gene/transcript or target SNP site, sequential polynucleotides thatcover the full-length sequence of a gene/transcript; or uniquepolynucleotides selected from particular areas along the length of atarget gene/transcript sequence, particularly areas corresponding to oneor more SNPs disclosed in Table 1 and/or Table 2. Polynucleotides usedin the microarray or detection kit can be specific to a SNP or SNPs ofinterest (e.g., specific to a particular SNP allele at a target SNPsite, or specific to particular SNP alleles at multiple different SNPsites), or specific to a polymorphic gene/transcript orgenes/transcripts of interest.

Hybridization assays based on polynucleotide arrays rely on thedifferences in hybridization stability of the probes to perfectlymatched and mismatched target sequence variants. For SNP genotyping, itis generally preferable that stringency conditions used in hybridizationassays are high enough such that nucleic acid molecules that differ fromone another at as little as a single SNP position can be differentiated(e.g., typical SNP hybridization assays are designed so thathybridization will occur only if one particular nucleotide is present ata SNP position, but will not occur if an alternative nucleotide ispresent at that SNP position). Such high stringency conditions may bepreferable when using, for example, nucleic acid arrays ofallele-specific probes for SNP detection. Such high stringencyconditions are described in the preceding section, and are well known tothose skilled in the art and can be found in, for example, CurrentProtocols in Molecular Biology, John Wiley & Sons, N.Y. (1989),6.3.1-6.3.6.

In other embodiments, the arrays are used in conjunction withchemiluminescent detection technology. The following patents and patentapplications, which are all hereby incorporated by reference, provideadditional information pertaining to chemiluminescent detection: U.S.patent application Ser. Nos. 10/620,332 and 10/620,333 describechemiluminescent approaches for microarray detection; U.S. Pat. Nos.6,124,478, 6,107,024, 5,994,073, 5,981,768, 5,871,938, 5,843,681,5,800,999, and 5,773,628 describe methods and compositions of dioxetanefor performing chemiluminescent detection; and U.S. publishedapplication US2002/0110828 discloses methods and compositions formicroarray controls.

In one embodiment of the invention, a nucleic acid array can comprise anarray of probes of about 15-25 nucleotides in length. In furtherembodiments, a nucleic acid array can comprise any number of probes, inwhich at least one probe is capable of detecting one or more SNPsdisclosed in Table 1 and/or Table 2, and/or at least one probe comprisesa fragment of one of the sequences selected from the group consisting ofthose disclosed in Table 1, Table 2, the Sequence Listing, and sequencescomplementary thereto, said fragment comprising at least about 8consecutive nucleotides, preferably 10, 12, 15, 16, 18, 20, morepreferably 22, 25, 30, 40, 47, 50, 55, 60, 65, 70, 80, 90, 100, or moreconsecutive nucleotides (or any other number in-between) and containing(or being complementary to) a novel SNP allele disclosed in Table 1and/or Table 2. In some embodiments, the nucleotide complementary to theSNP site is within 5, 4, 3, 2, or 1 nucleotide from the center of theprobe, more preferably at the center of said probe.

A polynucleotide probe can be synthesized on the surface of thesubstrate by using a chemical coupling procedure and an ink jetapplication apparatus, as described in PCT application WO95/251116(Baldeschweiler et al.) which is incorporated herein in its entirety byreference. In another aspect, a “gridded” array analogous to a dot (orslot) blot may be used to arrange and link cDNA fragments oroligonucleotides to the surface of a substrate using a vacuum system,thermal, UV, mechanical or chemical bonding procedures. An array, suchas those described above, may be produced by hand or by using availabledevices (slot blot or dot blot apparatus), materials (any suitable solidsupport), and machines (including robotic instruments), and may contain8, 24, 96, 384, 1536, 6144 or more polynucleotides, or any other numberwhich lends itself to the efficient use of commercially availableinstrumentation.

Using such arrays or other kits/systems, the present invention providesmethods of identifying the SNPs disclosed herein in a test sample. Suchmethods typically involve incubating a test sample of nucleic acids withan array comprising one or more probes corresponding to at least one SNPposition of the present invention, and assaying for binding of a nucleicacid from the test sample with one or more of the probes. Conditions forincubating a SNP detection reagent (or a kit/system that employs one ormore such SNP detection reagents) with a test sample vary. Incubationconditions depend on such factors as the format employed in the assay,the detection methods employed, and the type and nature of the detectionreagents used in the assay. One skilled in the art will recognize thatany one of the commonly available hybridization, amplification and arrayassay formats can readily be adapted to detect the SNPs disclosedherein.

A SNP detection kit/system of the present invention may includecomponents that are used to prepare nucleic acids from a test sample forthe subsequent amplification and/or detection of a SNP-containingnucleic acid molecule. Such sample preparation components can be used toproduce nucleic acid extracts (including DNA and/or RNA), proteins ormembrane extracts from any bodily fluids (such as blood, serum, plasma,urine, saliva, phlegm, gastric juices, semen, tears, sweat, etc.), skin,hair, cells (especially nucleated cells), biopsies, buccal swabs ortissue specimens. The test samples used in the above-described methodswill vary based on such factors as the assay format, nature of thedetection method, and the specific tissues, cells or extracts used asthe test sample to be assayed. Methods of preparing nucleic acids,proteins, and cell extracts are well known in the art and can be readilyadapted to obtain a sample that is compatible with the system utilized.Automated sample preparation systems for extracting nucleic acids from atest sample are commercially available, and examples are Qiagen'sBioRobot 9600, Applied Biosystems' PRISM 6700, and Roche MolecularSystems' COBAS AmpliPrep System.

Another form of kit contemplated by the present invention is acompartmentalized kit. A compartmentalized kit includes any kit in whichreagents are contained in separate containers. Such containers include,for example, small glass containers, plastic containers, strips ofplastic, glass or paper, or arraying material such as silica. Suchcontainers allow one to efficiently transfer reagents from onecompartment to another compartment such that the test samples andreagents are not cross-contaminated, or from one container to anothervessel not included in the kit, and the agents or solutions of eachcontainer can be added in a quantitative fashion from one compartment toanother or to another vessel. Such containers may include, for example,one or more containers which will accept the test sample, one or morecontainers which contain at least one probe or other SNP detectionreagent for detecting one or more SNPs of the present invention, one ormore containers which contain wash reagents (such as phosphate bufferedsaline, Tris-buffers, etc.), and one or more containers which containthe reagents used to reveal the presence of the bound probe or other SNPdetection reagents. The kit can optionally further comprise compartmentsand/or reagents for, for example, nucleic acid amplification or otherenzymatic reactions such as primer extension reactions, hybridization,ligation, electrophoresis (preferably capillary electrophoresis), massspectrometry, and/or laser-induced fluorescent detection. The kit mayalso include instructions for using the kit. Exemplary compartmentalizedkits include microfluidic devices known in the art (see, e.g., Weigl etal., “Lab-on-a-chip for drug development”, Adv Drug Deliv Rev. 2003 Feb.24; 55(3):349-77). In such microfluidic devices, the containers may bereferred to as, for example, microfluidic “compartments”, “chambers”, or“channels”.

Microfluidic devices, which may also be referred to as “lab-on-a-chip”systems, biomedical micro-electro-mechanical systems (bioMEMs), ormulticomponent integrated systems, are exemplary kits/systems of thepresent invention for analyzing SNPs. Such systems miniaturize andcompartmentalize processes such as probe/target hybridization, nucleicacid amplification, and capillary electrophoresis reactions in a singlefunctional device. Such microfluidic devices typically utilize detectionreagents in at least one aspect of the system, and such detectionreagents may be used to detect one or more SNPs of the presentinvention. One example of a microfluidic system is disclosed in U.S.Pat. No. 5,589,136, which describes the integration of PCR amplificationand capillary electrophoresis in chips. Exemplary microfluidic systemscomprise a pattern of microchannels designed onto a glass, silicon,quartz, or plastic wafer included on a microchip. The movements of thesamples may be controlled by electric, electroosmotic or hydrostaticforces applied across different areas of the microchip to createfunctional microscopic valves and pumps with no moving parts. Varyingthe voltage can be used as a means to control the liquid flow atintersections between the micro-machined channels and to change theliquid flow rate for pumping across different sections of the microchip.See, for example, U.S. Pat. No. 6,153,073, Dubrow et al., and U.S. Pat.No. 6,156,181, Parce et al.

For genotyping SNPs, an exemplary microfluidic system may integrate, forexample, nucleic acid amplification, primer extension, capillaryelectrophoresis, and a detection method such as laser inducedfluorescence detection. In a first step of an exemplary process forusing such an exemplary system, nucleic acid samples are amplified,preferably by PCR. Then, the amplification products are subjected toautomated primer extension reactions using ddNTPs (specific fluorescencefor each ddNTP) and the appropriate oligonucleotide primers to carry outprimer extension reactions which hybridize just upstream of the targetedSNP. Once the extension at the 3′ end is completed, the primers areseparated from the unincorporated fluorescent ddNTPs by capillaryelectrophoresis. The separation medium used in capillary electrophoresiscan be, for example, polyacrylamide, polyethyleneglycol or dextran. Theincorporated ddNTPs in the single nucleotide primer extension productsare identified by laser-induced fluorescence detection. Such anexemplary microchip can be used to process, for example, at least 96 to384 samples, or more, in parallel.

Uses of Nucleic Acid Molecules

The nucleic acid molecules of the present invention have a variety ofuses, especially in predicting an individual's risk for developing acardiovascular disorder (particularly the risk for experiencing a firstor recurrent acute coronary event such as a myocardial infarction orstroke), for prognosing the progression of a cardiovascular disorder inan individual (e.g., the severity or consequences of an acute coronaryevent), in evaluating the likelihood of an individual who has acardiovascular disorder of responding to treatment of the cardiovasculardisorder with statin, and/or predicting the likelihood that theindividual will experience toxicity or other undesirable side effectsfrom the statin treatment, etc. For example, the nucleic acid moleculesare useful as hybridization probes, such as for genotyping SNPs inmessenger RNA, transcript, cDNA, genomic DNA, amplified DNA or othernucleic acid molecules, and for isolating full-length cDNA and genomicclones encoding the variant peptides disclosed in Table 1 as well astheir orthologs.

A probe can hybridize to any nucleotide sequence along the entire lengthof a nucleic acid molecule provided in Table 1 and/or Table 2.Preferably, a probe of the present invention hybridizes to a region of atarget sequence that encompasses a SNP position indicated in Table 1and/or Table 2. More preferably, a probe hybridizes to a SNP-containingtarget sequence in a sequence-specific manner such that it distinguishesthe target sequence from other nucleotide sequences which vary from thetarget sequence only by which nucleotide is present at the SNP site.Such a probe is particularly useful for detecting the presence of aSNP-containing nucleic acid in a test sample, or for determining whichnucleotide (allele) is present at a particular SNP site (i.e.,genotyping the SNP site).

A nucleic acid hybridization probe may be used for determining thepresence, level, form, and/or distribution of nucleic acid expression.The nucleic acid whose level is determined can be DNA or RNA.Accordingly, probes specific for the SNPs described herein can be usedto assess the presence, expression and/or gene copy number in a givencell, tissue, or organism. These uses are relevant for diagnosis ofdisorders involving an increase or decrease in gene expression relativeto normal levels. In vitro techniques for detection of mRNA include, forexample, Northern blot hybridizations and in situ hybridizations. Invitro techniques for detecting DNA include Southern blot hybridizationsand in situ hybridizations (Sambrook and Russell, 2000, MolecularCloning: A Laboratory Manual, Cold Spring Harbor Press, Cold SpringHarbor, N.Y.).

Probes can be used as part of a diagnostic test kit for identifyingcells or tissues in which a variant protein is expressed, such as bymeasuring the level of a variant protein-encoding nucleic acid (e.g.,mRNA) in a sample of cells from a subject or determining if apolynucleotide contains a SNP of interest.

Thus, the nucleic acid molecules of the invention can be used ashybridization probes to detect the SNPs disclosed herein, therebydetermining whether an individual with the polymorphisms is likely orunlikely to develop a cardiovascular disorder such as an acute coronaryevent, or the likelihood that an individual will respond positively tostatin treatment of a cardiovascular disorder. Detection of a SNPassociated with a disease phenotype provides a diagnostic tool for anactive disease and/or genetic predisposition to the disease.

Furthermore, the nucleic acid molecules of the invention are thereforeuseful for detecting a gene (gene information is disclosed in Table 2,for example) which contains a SNP disclosed herein and/or products ofsuch genes, such as expressed mRNA transcript molecules (transcriptinformation is disclosed in Table 1, for example), and are thus usefulfor detecting gene expression. The nucleic acid molecules can optionallybe implemented in, for example, an array or kit format for use indetecting gene expression.

The nucleic acid molecules of the invention are also useful as primersto amplify any given region of a nucleic acid molecule, particularly aregion containing a SNP identified in Table 1 and/or Table 2.

The nucleic acid molecules of the invention are also useful forconstructing recombinant vectors (described in greater detail below).Such vectors include expression vectors that express a portion of, orall of, any of the variant peptide sequences provided in Table 1.Vectors also include insertion vectors, used to integrate into anothernucleic acid molecule sequence, such as into the cellular genome, toalter in situ expression of a gene and/or gene product. For example, anendogenous coding sequence can be replaced via homologous recombinationwith all or part of the coding region containing one or morespecifically introduced SNPs.

The nucleic acid molecules of the invention are also useful forexpressing antigenic portions of the variant proteins, particularlyantigenic portions that contain a variant amino acid sequence (e.g., anamino acid substitution) caused by a SNP disclosed in Table 1 and/orTable 2.

The nucleic acid molecules of the invention are also useful forconstructing vectors containing a gene regulatory region of the nucleicacid molecules of the present invention.

The nucleic acid molecules of the invention are also useful fordesigning ribozymes corresponding to all, or a part, of an mRNA moleculeexpressed from a SNP-containing nucleic acid molecule described herein.

The nucleic acid molecules of the invention are also useful forconstructing host cells expressing a part, or all, of the nucleic acidmolecules and variant peptides.

The nucleic acid molecules of the invention are also useful forconstructing transgenic animals expressing all, or a part, of thenucleic acid molecules and variant peptides. The production ofrecombinant cells and transgenic animals having nucleic acid moleculeswhich contain the SNPs disclosed in Table 1 and/or Table 2 allow, forexample, effective clinical design of treatment compounds and dosageregimens.

The nucleic acid molecules of the invention are also useful in assaysfor drug screening to identify compounds that, for example, modulatenucleic acid expression.

The nucleic acid molecules of the invention are also useful in genetherapy in patients whose cells have aberrant gene expression. Thus,recombinant cells, which include a patient's cells that have beenengineered ex vivo and returned to the patient, can be introduced intoan individual where the recombinant cells produce the desired protein totreat the individual.

SNP Genotyping Methods

The process of determining which specific nucleotide (i.e., allele) ispresent at each of one or more SNP positions, such as a SNP position ina nucleic acid molecule disclosed in Table 1 and/or Table 2, is referredto as SNP genotyping. The present invention provides methods of SNPgenotyping, such as for use in evaluating an individual's risk fordeveloping a cardiovascular disease—particularly an acute coronary event(such as myocardial infarction or stroke) and for evaluating anindividual's prognosis for disease severity and recovery, for predictingthe likelihood that an individual who has previously experienced anacute coronary event will experience one or more recurrent acutecoronary events, for implementing a preventive or treatment regimen foran individual based on that individual having an increasedsusceptibility for developing a cardiovascular disorder (e.g., increasedrisk for experiencing one or more myocardial infarctions or strokes), inevaluating an individual's likelihood of responding to statin treatmentfor cardiovascular disease, in selecting a treatment regimen (e.g., indeciding whether or not to administer statin treatment to an individualhaving a cardiovascular disease, or in formulating or selecting aparticular statin-based treatment regimen such as dosage and/orfrequency of administration of statin treatment or choosing whichform/type of statin to be administered such as a particularpharmaceutical composition or compound, etc.), determining thelikelihood of experiencing toxicity or other undesirable side effectsfrom the statin treatment, or selecting individuals for a clinical trialof a statin (e.g., selecting individuals to participate in the trial whoare most likely to respond positively from the statin treatment), etc.

Nucleic acid samples can be genotyped to determine which allele(s)is/are present at any given genetic region (e.g., SNP position) ofinterest by methods well known in the art. The neighboring sequence canbe used to design SNP detection reagents such as oligonucleotide probes,which may optionally be implemented in a kit format. Exemplary SNPgenotyping methods are described in Chen et al., “Single nucleotidepolymorphism genotyping: biochemistry, protocol, cost and throughput”,Pharmacogenomics J. 2003; 3(2):77-96; Kwok et al., “Detection of singlenucleotide polymorphisms”, Curr Issues Mol Biol. 2003 April; 5(2):43-60;Shi, “Technologies for individual genotyping: detection of geneticpolymorphisms in drug targets and disease genes”, Am J Pharmacogenomics.2002; 2(3):197-205; and Kwok, “Methods for genotyping single nucleotidepolymorphisms”, Annu Rev Genomics Hum Genet 2001; 2:235-58. Exemplarytechniques for high-throughput SNP genotyping are described inMarnellos, “High-throughput SNP analysis for genetic associationstudies”, Curr Opin Drug Discov Devel. 2003 May; 6(3):317-21. Common SNPgenotyping methods include, but are not limited to, TaqMan assays,molecular beacon assays, nucleic acid arrays, allele-specific primerextension, allele-specific PCR, arrayed primer extension, homogeneousprimer extension assays, primer extension with detection by massspectrometry, pyrosequencing, multiplex primer extension sorted ongenetic arrays, ligation with rolling circle amplification, homogeneousligation, OLA (U.S. Pat. No. 4,988,167), multiplex ligation reactionsorted on genetic arrays, restriction-fragment length polymorphism,single base extension-tag assays, and the Invader assay. Such methodsmay be used in combination with detection mechanisms such as, forexample, luminescence or chemiluminescence detection, fluorescencedetection, time-resolved fluorescence detection, fluorescence resonanceenergy transfer, fluorescence polarization, mass spectrometry, andelectrical detection.

Various methods for detecting polymorphisms include, but are not limitedto, methods in which protection from cleavage agents is used to detectmismatched bases in RNA/RNA or RNA/DNA duplexes (Myers et al., Science230:1242 (1985); Cotton et al., PNAS 85:4397 (1988); and Saleeba et al.,Meth. Enzymol. 217:286-295 (1992)), comparison of the electrophoreticmobility of variant and wild type nucleic acid molecules (Orita et al.,PNAS 86:2766 (1989); Cotton et al., Mutat. Res. 285:125-144 (1993); andHayashi et al., Genet. Anal. Tech. Appl. 9:73-79 (1992)), and assayingthe movement of polymorphic or wild-type fragments in polyacrylamidegels containing a gradient of denaturant using denaturing gradient gelelectrophoresis (DGGE) (Myers et al., Nature 313:495 (1985)). Sequencevariations at specific locations can also be assessed by nucleaseprotection assays such as RNase and S1 protection or chemical cleavagemethods.

In a preferred embodiment, SNP genotyping is performed using the TaqManassay, which is also known as the 5′ nuclease assay (U.S. Pat. Nos.5,210,015 and 5,538,848). The TaqMan assay detects the accumulation of aspecific amplified product during PCR. The TaqMan assay utilizes anoligonucleotide probe labeled with a fluorescent reporter dye and aquencher dye. The reporter dye is excited by irradiation at anappropriate wavelength, it transfers energy to the quencher dye in thesame probe via a process called fluorescence resonance energy transfer(FRET). When attached to the probe, the excited reporter dye does notemit a signal. The proximity of the quencher dye to the reporter dye inthe intact probe maintains a reduced fluorescence for the reporter. Thereporter dye and quencher dye may be at the 5′ most and the 3′ mostends, respectively, or vice versa. Alternatively, the reporter dye maybe at the 5′ or 3′ most end while the quencher dye is attached to aninternal nucleotide, or vice versa. In yet another embodiment, both thereporter and the quencher may be attached to internal nucleotides at adistance from each other such that fluorescence of the reporter isreduced.

During PCR, the 5′ nuclease activity of DNA polymerase cleaves theprobe, thereby separating the reporter dye and the quencher dye andresulting in increased fluorescence of the reporter. Accumulation of PCRproduct is detected directly by monitoring the increase in fluorescenceof the reporter dye. The DNA polymerase cleaves the probe between thereporter dye and the quencher dye only if the probe hybridizes to thetarget SNP-containing template which is amplified during PCR, and theprobe is designed to hybridize to the target SNP site only if aparticular SNP allele is present.

Preferred TaqMan primer and probe sequences can readily be determinedusing the SNP and associated nucleic acid sequence information providedherein. A number of computer programs, such as Primer Express (AppliedBiosystems, Foster City, Calif.), can be used to rapidly obtain optimalprimer/probe sets. It will be apparent to one of skill in the art thatsuch primers and probes for detecting the SNPs of the present inventionare useful in screening for individuals who are susceptible todeveloping a cardiovascular disorder (e.g., an acute coronary event) orin screening individuals who have a cardiovascular disorder for theirlikelihood of responding to statin treatment. These probes and primerscan be readily incorporated into a kit format. The present inventionalso includes modifications of the Taqman assay well known in the artsuch as the use of Molecular Beacon probes (U.S. Pat. Nos. 5,118,801 and5,312,728) and other variant formats (U.S. Pat. Nos. 5,866,336 and6,117,635).

Another preferred method for genotyping the SNPs of the presentinvention is the use of two oligonucleotide probes in an OLA (see, e.g.,U.S. Pat. No. 4,988,617). In this method, one probe hybridizes to asegment of a target nucleic acid with its 3′ most end aligned with theSNP site. A second probe hybridizes to an adjacent segment of the targetnucleic acid molecule directly 3′ to the first probe. The two juxtaposedprobes hybridize to the target nucleic acid molecule, and are ligated inthe presence of a linking agent such as a ligase if there is perfectcomplementarity between the 3′ most nucleotide of the first probe withthe SNP site. If there is a mismatch, ligation would not occur. Afterthe reaction, the ligated probes are separated from the target nucleicacid molecule, and detected as indicators of the presence of a SNP.

The following patents, patent applications, and published internationalpatent applications, which are all hereby incorporated by reference,provide additional information pertaining to techniques for carrying outvarious types of OLA: U.S. Pat. Nos. 6,027,889, 6,268,148, 5,494,810,5,830,711, and 6,054,564 describe OLA strategies for performing SNPdetection; WO 97/31256 and WO 00/56927 describe OLA strategies forperforming SNP detection using universal arrays, wherein a zipcodesequence can be introduced into one of the hybridization probes, and theresulting product, or amplified product, hybridized to a universal zipcode array; U.S. Pat. No. 117,329 (and U.S. Pat. No. 9,584,905)describes OLA (or LDR) followed by PCR, wherein zipcodes areincorporated into OLA probes, and amplified PCR products are determinedby electrophoretic or universal zipcode array readout; U.S. applications60/427,818, 60/445,636, and 60/445,494 describe SNPlex methods andsoftware for multiplexed SNP detection using OLA followed by PCR,wherein zipcodes are incorporated into OLA probes, and amplified PCRproducts are hybridized with a zipchute reagent, and the identity of theSNP determined from electrophoretic readout of the zipchute. In someembodiments, OLA is carried out prior to PCR (or another method ofnucleic acid amplification). In other embodiments, PCR (or anothermethod of nucleic acid amplification) is carried out prior to OLA.

Another method for SNP genotyping is based on mass spectrometry. Massspectrometry takes advantage of the unique mass of each of the fournucleotides of DNA. SNPs can be unambiguously genotyped by massspectrometry by measuring the differences in the mass of nucleic acidshaving alternative SNP alleles. MALDI-TOF (Matrix Assisted LaserDesorption Ionization—Time of Flight) mass spectrometry technology ispreferred for extremely precise determinations of molecular mass, suchas SNPs. Numerous approaches to SNP analysis have been developed basedon mass spectrometry. Preferred mass spectrometry-based methods of SNPgenotyping include primer extension assays, which can also be utilizedin combination with other approaches, such as traditional gel-basedformats and microarrays.

Typically, the primer extension assay involves designing and annealing aprimer to a template PCR amplicon upstream (5′) from a target SNPposition. A mix of dideoxynucleotide triphosphates (ddNTPs) and/ordeoxynucleotide triphosphates (dNTPs) are added to a reaction mixturecontaining template (e.g., a SNP-containing nucleic acid molecule whichhas typically been amplified, such as by PCR), primer, and DNApolymerase. Extension of the primer terminates at the first position inthe template where a nucleotide complementary to one of the ddNTPs inthe mix occurs. The primer can be either immediately adjacent (i.e., thenucleotide at the 3′ end of the primer hybridizes to the nucleotide nextto the target SNP site) or two or more nucleotides removed from the SNPposition. If the primer is several nucleotides removed from the targetSNP position, the only limitation is that the template sequence betweenthe 3′ end of the primer and the SNP position cannot contain anucleotide of the same type as the one to be detected, or this willcause premature termination of the extension primer. Alternatively, ifall four ddNTPs alone, with no dNTPs, are added to the reaction mixture,the primer will always be extended by only one nucleotide, correspondingto the target SNP position. In this instance, primers are designed tobind one nucleotide upstream from the SNP position (i.e., the nucleotideat the 3′ end of the primer hybridizes to the nucleotide that isimmediately adjacent to the target SNP site on the 5′ side of the targetSNP site). Extension by only one nucleotide is preferable, as itminimizes the overall mass of the extended primer, thereby increasingthe resolution of mass differences between alternative SNP nucleotides.Furthermore, mass-tagged ddNTPs can be employed in the primer extensionreactions in place of unmodified ddNTPs. This increases the massdifference between primers extended with these ddNTPs, thereby providingincreased sensitivity and accuracy, and is particularly useful fortyping heterozygous base positions. Mass-tagging also alleviates theneed for intensive sample-preparation procedures and decreases thenecessary resolving power of the mass spectrometer.

The extended primers can then be purified and analyzed by MALDI-TOF massspectrometry to determine the identity of the nucleotide present at thetarget SNP position. In one method of analysis, the products from theprimer extension reaction are combined with light absorbing crystalsthat form a matrix. The matrix is then hit with an energy source such asa laser to ionize and desorb the nucleic acid molecules into thegas-phase. The ionized molecules are then ejected into a flight tube andaccelerated down the tube towards a detector. The time between theionization event, such as a laser pulse, and collision of the moleculewith the detector is the time of flight of that molecule. The time offlight is precisely correlated with the mass-to-charge ratio (m/z) ofthe ionized molecule. Ions with smaller m/z travel down the tube fasterthan ions with larger m/z and therefore the lighter ions reach thedetector before the heavier ions. The time-of-flight is then convertedinto a corresponding, and highly precise, m/z. In this manner, SNPs canbe identified based on the slight differences in mass, and thecorresponding time of flight differences, inherent in nucleic acidmolecules having different nucleotides at a single base position. Forfurther information regarding the use of primer extension assays inconjunction with MALDI-TOF mass spectrometry for SNP genotyping, see,e.g., Wise et al., “A standard protocol for single nucleotide primerextension in the human genome using matrix-assisted laserdesorption/ionization time-of-flight mass spectrometry”, Rapid CommunMass Spectrom. 2003; 17(11):1195-202.

The following references provide further information describing massspectrometry-based methods for SNP genotyping: Bocker, “SNP and mutationdiscovery using base-specific cleavage and MALDI-TOF mass spectrometry”,Bioinformatics. 2003 July; 19 Suppl 1:144-153; Storm et al., “MALDI-TOFmass spectrometry-based SNP genotyping”, Methods Mol Biol. 2003;212:241-62; Jurinke et al., “The use of MassARRAY technology for highthroughput genotyping”, Adv Biochem Eng Biotechnol. 2002; 77:57-74; andJurinke et al., “Automated genotyping using the DNA MassArraytechnology”, Methods Mol Biol. 2002; 187:179-92.

SNPs can also be scored by direct DNA sequencing. A variety of automatedsequencing procedures can be utilized ((1995) Biotechniques 19:448),including sequencing by mass spectrometry (see, e.g., PCT InternationalPublication No. WO94/16101; Cohen et al., Adv. Chromatogr. 36:127-162(1996); and Griffin et al., Appl. Biochem. Biotechnol. 38:147-159(1993)). The nucleic acid sequences of the present invention enable oneof ordinary skill in the art to readily design sequencing primers forsuch automated sequencing procedures. Commercial instrumentation, suchas the Applied Biosystems 377, 3100, 3700, 3730, and 3730×l DNAAnalyzers (Foster City, Calif.), is commonly used in the art forautomated sequencing.

Other methods that can be used to genotype the SNPs of the presentinvention include single-strand conformational polymorphism (SSCP), anddenaturing gradient gel electrophoresis (DGGE) (Myers et al., Nature313:495 (1985)). SSCP identifies base differences by alteration inelectrophoretic migration of single stranded PCR products, as describedin Orita et al., Proc. Nat. Acad. Single-stranded PCR products can begenerated by heating or otherwise denaturing double stranded PCRproducts. Single-stranded nucleic acids may refold or form secondarystructures that are partially dependent on the base sequence. Thedifferent electrophoretic mobilities of single-stranded amplificationproducts are related to base-sequence differences at SNP positions. DGGEdifferentiates SNP alleles based on the different sequence-dependentstabilities and melting properties inherent in polymorphic DNA and thecorresponding differences in electrophoretic migration patterns in adenaturing gradient gel (Erlich, ed., PCR Technology, Principles andApplications for DNA Amplification, W.H. Freeman and Co, New York, 1992,Chapter 7).

Sequence-specific ribozymes (U.S. Pat. No. 5,498,531) can also be usedto score SNPs based on the development or loss of a ribozyme cleavagesite. Perfectly matched sequences can be distinguished from mismatchedsequences by nuclease cleavage digestion assays or by differences inmelting temperature. If the SNP affects a restriction enzyme cleavagesite, the SNP can be identified by alterations in restriction enzymedigestion patterns, and the corresponding changes in nucleic acidfragment lengths determined by gel electrophoresis

SNP genotyping can include the steps of, for example, collecting abiological sample from a human subject (e.g., sample of tissues, cells,fluids, secretions, etc.), isolating nucleic acids (e.g., genomic DNA,mRNA or both) from the cells of the sample, contacting the nucleic acidswith one or more primers which specifically hybridize to a region of theisolated nucleic acid containing a target SNP under conditions such thathybridization and amplification of the target nucleic acid regionoccurs, and determining the nucleotide present at the SNP position ofinterest, or, in some assays, detecting the presence or absence of anamplification product (assays can be designed so that hybridizationand/or amplification will only occur if a particular SNP allele ispresent or absent). In some assays, the size of the amplificationproduct is detected and compared to the length of a control sample; forexample, deletions and insertions can be detected by a change in size ofthe amplified product compared to a normal genotype.

SNP genotyping is useful for numerous practical applications, asdescribed below. Examples of such applications include, but are notlimited to, SNP-disease association analysis, disease predispositionscreening, disease diagnosis, disease prognosis, disease progressionmonitoring, determining therapeutic strategies based on an individual'sgenotype (“pharmacogenomics”), developing therapeutic agents based onSNP genotypes associated with a disease or likelihood of responding to adrug, stratifying a patient population for clinical trial for atreatment regimen, predicting the likelihood that an individual willexperience toxic side effects from a therapeutic agent, and humanidentification applications such as forensics.

Analysis of Genetic Association Between SNPs and Phenotypic Traits

SNP genotyping for disease diagnosis, disease predisposition screening,disease prognosis, determining drug responsiveness (pharmacogenomics),drug toxicity screening, and other uses described herein, typicallyrelies on initially establishing a genetic association between one ormore specific SNPs and the particular phenotypic traits of interest.

Different study designs may be used for genetic association studies(Modern Epidemiology, Lippincott Williams & Wilkins (1998), 609-622).Observational studies are most frequently carried out in which theresponse of the patients is not interfered with. The first type ofobservational study identifies a sample of persons in whom the suspectedcause of the disease is present and another sample of persons in whomthe suspected cause is absent, and then the frequency of development ofdisease in the two samples is compared. These sampled populations arecalled cohorts, and the study is a prospective study. The other type ofobservational study is case-control or a retrospective study. In typicalcase-control studies, samples are collected from individuals with thephenotype of interest (cases) such as certain manifestations of adisease, and from individuals without the phenotype (controls) in apopulation (target population) that conclusions are to be drawn from.Then the possible causes of the disease are investigatedretrospectively. As the time and costs of collecting samples incase-control studies are considerably less than those for prospectivestudies, case-control studies are the more commonly used study design ingenetic association studies, at least during the exploration anddiscovery stage.

In both types of observational studies, there may be potentialconfounding factors that should be taken into consideration. Confoundingfactors are those that are associated with both the real cause(s) of thedisease and the disease itself, and they include demographic informationsuch as age, gender, ethnicity as well as environmental factors. Whenconfounding factors are not matched in cases and controls in a study,and are not controlled properly, spurious association results can arise.If potential confounding factors are identified, they should becontrolled for by analysis methods explained below.

In a genetic association study, the cause of interest to be tested is acertain allele or a SNP or a combination of alleles or a haplotype fromseveral SNPs. Thus, tissue specimens (e.g., whole blood) from thesampled individuals may be collected and genomic DNA genotyped for theSNP(s) of interest. In addition to the phenotypic trait of interest,other information such as demographic (e.g., age, gender, ethnicity,etc.), clinical, and environmental information that may influence theoutcome of the trait can be collected to further characterize and definethe sample set. In many cases, these factors are known to be associatedwith diseases and/or SNP allele frequencies. There are likelygene-environment and/or gene-gene interactions as well. Analysis methodsto address gene-environment and gene-gene interactions (for example, theeffects of the presence of both susceptibility alleles at two differentgenes can be greater than the effects of the individual alleles at twogenes combined) are discussed below.

After all the relevant phenotypic and genotypic information has beenobtained, statistical analyses are carried out to determine if there isany significant correlation between the presence of an allele or agenotype with the phenotypic characteristics of an individual.Preferably, data inspection and cleaning are first performed beforecarrying out statistical tests for genetic association. Epidemiologicaland clinical data of the samples can be summarized by descriptivestatistics with tables and graphs. Data validation is preferablyperformed to check for data completion, inconsistent entries, andoutliers. Chi-squared tests and t-tests (Wilcoxon rank-sum tests ifdistributions are not normal) may then be used to check for significantdifferences between cases and controls for discrete and continuousvariables, respectively. To ensure genotyping quality, Hardy-Weinbergdisequilibrium tests can be performed on cases and controls separately.Significant deviation from Hardy-Weinberg equilibrium (HWE) in bothcases and controls for individual markers can be indicative ofgenotyping errors. If HWE is violated in a majority of markers, it isindicative of population substructure that should be furtherinvestigated. Moreover, Hardy-Weinberg disequilibrium in cases only canindicate genetic association of the markers with the disease (GeneticData Analysis, Weir B., Sinauer (1990)).

To test whether an allele of a single SNP is associated with the case orcontrol status of a phenotypic trait, one skilled in the art can compareallele frequencies in cases and controls. Standard chi-squared tests andFisher exact tests can be carried out on a 2×2 table (2 SNP alleles×2outcomes in the categorical trait of interest). To test whethergenotypes of a SNP are associated, chi-squared tests can be carried outon a 3×2 table (3 genotypes×2 outcomes). Score tests are also carriedout for genotypic association to contrast the three genotypicfrequencies (major homozygotes, heterozygotes and minor homozygotes) incases and controls, and to look for trends using 3 different modes ofinheritance, namely dominant (with contrast coefficients 2, −1, −1),additive (with contrast coefficients 1, 0, −1) and recessive (withcontrast coefficients 1, 1, −2). Odds ratios for minor versus majoralleles, and odds ratios for heterozygote and homozygote variants versusthe wild type genotypes are calculated with the desired confidencelimits, usually 95%.

In order to control for confounders and to test for interaction andeffect modifiers, stratified analyses may be performed using stratifiedfactors that are likely to be confounding, including demographicinformation such as age, ethnicity, and gender, or an interactingelement or effect modifier, such as a known major gene (e.g., APOE forAlzheimer's disease or HLA genes for autoimmune diseases), orenvironmental factors such as smoking in lung cancer. Stratifiedassociation tests may be carried out using Cochran-Mantel-Haenszel teststhat take into account the ordinal nature of genotypes with 0, 1, and 2variant alleles. Exact tests by StatXact may also be performed whencomputationally possible. Another way to adjust for confounding effectsand test for interactions is to perform stepwise multiple logisticregression analysis using statistical packages such as SAS or R.Logistic regression is a model-building technique in which the bestfitting and most parsimonious model is built to describe the relationbetween the dichotomous outcome (for instance, getting a certain diseaseor not) and a set of independent variables (for instance, genotypes ofdifferent associated genes, and the associated demographic andenvironmental factors). The most common model is one in which the logittransformation of the odds ratios is expressed as a linear combinationof the variables (main effects) and their cross-product terms(interactions) (Applied Logistic Regression, Hosmer and Lemeshow, Wiley(2000)). To test whether a certain variable or interaction issignificantly associated with the outcome, coefficients in the model arefirst estimated and then tested for statistical significance of theirdeparture from zero.

In addition to performing association tests one marker at a time,haplotype association analysis may also be performed to study a numberof markers that are closely linked together. Haplotype association testscan have better power than genotypic or allelic association tests whenthe tested markers are not the disease-causing mutations themselves butare in linkage disequilibrium with such mutations. The test will even bemore powerful if the disease is indeed caused by a combination ofalleles on a haplotype (e.g., APOE is a haplotype formed by 2 SNPs thatare very close to each other). In order to perform haplotype associationeffectively, marker-marker linkage disequilibrium measures, both D′ andR², are typically calculated for the markers within a gene to elucidatethe haplotype structure. Recent studies (Daly et al, Nature Genetics,29, 232-235, 2001) in linkage disequilibrium indicate that SNPs within agene are organized in block pattern, and a high degree of linkagedisequilibrium exists within blocks and very little linkagedisequilibrium exists between blocks. Haplotype association with thedisease status can be performed using such blocks once they have beenelucidated.

Haplotype association tests can be carried out in a similar fashion asthe allelic and genotypic association tests. Each haplotype in a gene isanalogous to an allele in a multi-allelic marker. One skilled in the artcan either compare the haplotype frequencies in cases and controls ortest genetic association with different pairs of haplotypes. It has beenproposed (Schaid et al, Am. J. Hum. Genet., 70, 425-434, 2002) thatscore tests can be done on haplotypes using the program “haplo.score”.In that method, haplotypes are first inferred by EM algorithm and scoretests are carried out with a generalized linear model (GLM) frameworkthat allows the adjustment of other factors.

An important decision in the performance of genetic association tests isthe determination of the significance level at which significantassociation can be declared when the p-value of the tests reaches thatlevel. In an exploratory analysis where positive hits will be followedup in subsequent confirmatory testing, an unadjusted p-value <0.1 (asignificance level on the lenient side) may be used for generatinghypotheses for significant association of a SNP with certain phenotypiccharacteristics of a disease. It is preferred that a p-value <0.05 (asignificance level traditionally used in the art) is achieved in orderfor a SNP to be considered to have an association with a disease. It ismore preferred that a p-value <0.01 (a significance level on thestringent side) is achieved for an association to be declared. When hitsare followed up in confirmatory analyses in more samples of the samesource or in different samples from different sources, adjustment formultiple testing will be performed as to avoid excess number of hitswhile maintaining the experiment-wise error rates at 0.05. While thereare different methods to adjust for multiple testing to control fordifferent kinds of error rates, a commonly used but rather conservativemethod is Bonferroni correction to control the experiment-wise orfamily-wise error rate (Multiple comparisons and multiple tests,Westfall et al, SAS Institute (1999)). Permutation tests to control forthe false discovery rates, FDR, can be more powerful (Benjamini andHochberg, Journal of the Royal Statistical Society, Series B 57,1289-1300, 1995, Resampling-based Multiple Testing, Westfall and Young,Wiley (1993)). Such methods to control for multiplicity would bepreferred when the tests are dependent and controlling for falsediscovery rates is sufficient as opposed to controlling for theexperiment-wise error rates.

In replication studies using samples from different populations afterstatistically significant markers have been identified in theexploratory stage, meta-analyses can then be performed by combiningevidence of different studies (Modern Epidemiology, Lippincott Williams& Wilkins, 1998, 643-673). If available, association results known inthe art for the same SNPs can be included in the meta-analyses.

Since both genotyping and disease status classification can involveerrors, sensitivity analyses may be performed to see how odds ratios andp-values would change upon various estimates on genotyping and diseaseclassification error rates.

It has been well known that subpopulation-based sampling bias betweencases and controls can lead to spurious results in case-controlassociation studies (Ewens and Spielman, Am. J. Hum. Genet. 62, 450-458,1995) when prevalence of the disease is associated with differentsubpopulation groups. Such bias can also lead to a loss of statisticalpower in genetic association studies. To detect populationstratification, Pritchard and Rosenberg (Pritchard et al. Am. J. Hum.Gen. 1999, 65:220-228) suggested typing markers that are unlinked to thedisease and using results of association tests on those markers todetermine whether there is any population stratification. Whenstratification is detected, the genomic control (GC) method as proposedby Devlin and Roeder (Devlin et al. Biometrics 1999, 55:997-1004) can beused to adjust for the inflation of test statistics due to populationstratification. GC method is robust to changes in population structurelevels as well as being applicable to DNA pooling designs (Devlin et al.Genet. Epidem. 20001, 21:273-284).

While Pritchard's method recommended using 15-20 unlinked microsatellitemarkers, it suggested using more than 30 biallelic markers to get enoughpower to detect population stratification. For the GC method, it hasbeen shown (Bacanu et al. Am. J. Hum. Genet. 2000, 66:1933-1944) thatabout 60-70 biallelic markers are sufficient to estimate the inflationfactor for the test statistics due to population stratification. Hence,70 intergenic SNPs can be chosen in unlinked regions as indicated in agenome scan (Kehoe et al. Hum. Mol. Genet. 1999, 8:237-245).

Once individual risk factors, genetic or non-genetic, have been foundfor the predisposition to disease, the next step is to set up aclassification/prediction scheme to predict the category (for instance,disease or no-disease) that an individual will be in depending on hisgenotypes of associated SNPs and other non-genetic risk factors.Logistic regression for discrete trait and linear regression forcontinuous trait are standard techniques for such tasks (AppliedRegression Analysis, Draper and Smith, Wiley (1998)). Moreover, othertechniques can also be used for setting up classification. Suchtechniques include, but are not limited to, MART, CART, neural network,and discriminant analyses that are suitable for use in comparing theperformance of different methods (The Elements of Statistical Learning,Hastie, Tibshirani & Friedman, Springer (2002)).

Disease Diagnosis and Predisposition Screening

Information on association/correlation between genotypes anddisease-related phenotypes can be exploited in several ways. Forexample, in the case of a highly statistically significant associationbetween one or more SNPs with predisposition to a disease for whichtreatment is available, detection of such a genotype pattern in anindividual may justify immediate administration of treatment, or atleast the institution of regular monitoring of the individual. Detectionof the susceptibility alleles associated with serious disease in acouple contemplating having children may also be valuable to the couplein their reproductive decisions. In the case of a weaker but stillstatistically significant association between a SNP and a human disease,immediate therapeutic intervention or monitoring may not be justifiedafter detecting the susceptibility allele or SNP. Nevertheless, thesubject can be motivated to begin simple life-style changes (e.g., diet,exercise) that can be accomplished at little or no cost to theindividual but would confer potential benefits in reducing the risk ofdeveloping conditions for which that individual may have an increasedrisk by virtue of having the susceptibility allele(s).

The SNPs of the invention may contribute to cardiovascular disorderssuch as acute coronary events, or to responsiveness of an individual tostatin treatment, in different ways. Some polymorphisms occur within aprotein coding sequence and contribute to disease phenotype by affectingprotein structure. Other polymorphisms occur in noncoding regions butmay exert phenotypic effects indirectly via influence on, for example,replication, transcription, and/or translation. A single SNP may affectmore than one phenotypic trait. Likewise, a single phenotypic trait maybe affected by multiple SNPs in different genes.

As used herein, the terms “diagnose”, “diagnosis”, and “diagnostics”include, but are not limited to any of the following: detection of acardiovascular disorders that an individual may presently have,predisposition/susceptibility screening (e.g., determining whether anindividual has an increased risk of experiencing an acute coronary eventin the future, or determining whether an individual has a decreased riskof experiencing an acute coronary event in the future), determining aparticular type or subclass of cardiovascular disorder in an individualknown to currently have or to have previously experienced acardiovascular disorder, confirming or reinforcing a previously madediagnosis of a cardiovascular disorder, evaluating an individual'slikelihood of responding to statin treatment for cardiovasculardisorders, predisposition screening (e.g., evaluating an individual'slikelihood of responding to statin treatment if the individual were todevelop a cardiovascular disorder in the future), determining aparticular type or subclass of responder/non-responder in an individualknown to respond or not respond to statin treatment, confirming orreinforcing a previously made classification of an individual as aresponder/non-responder to statin treatment, pharmacogenomic evaluationof an individual to determine which therapeutic strategy that individualis most likely to positively respond to or to predict whether a patientis likely to respond to a particular treatment such as statin treatment,predicting whether a patient is likely to experience toxic effects froma particular treatment or therapeutic compound, and evaluating thefuture prognosis of an individual having a cardiovascular disorder. Suchdiagnostic uses are based on the SNPs individually or in a uniquecombination or SNP haplotypes of the present invention.

Haplotypes are particularly useful in that, for example, fewer SNPs canbe genotyped to determine if a particular genomic region harbors a locusthat influences a particular phenotype, such as in linkagedisequilibrium-based SNP association analysis.

Linkage disequilibrium (LD) refers to the co-inheritance of alleles(e.g., alternative nucleotides) at two or more different SNP sites atfrequencies greater than would be expected from the separate frequenciesof occurrence of each allele in a given population. The expectedfrequency of co-occurrence of two alleles that are inheritedindependently is the frequency of the first_allele multiplied by thefrequency of the second allele. Alleles that co-occur at expectedfrequencies are said to be in “linkage equilibrium”. In contrast, LDrefers to any non-random genetic association between allele(s) at two ormore different SNP sites, which is generally due to the physicalproximity of the two loci along a chromosome. LD can occur when two ormore SNPs sites are in close physical proximity to each other on a givenchromosome and therefore alleles at these SNP sites will tend to remainunseparated for multiple generations with the consequence that aparticular nucleotide (allele) at one SNP site will show a non-randomassociation with a particular nucleotide (allele) at a different SNPsite located nearby. Hence, genotyping one of the SNP sites will givealmost the same information as genotyping the other SNP site that is inLD.

Various degrees of LD can be encountered between two or more SNPs withthe result being that some SNPs are more closely associated (i.e., instronger LD) than others. Furthermore, the physical distance over whichLD extends along a chromosome differs between different regions of thegenome, and therefore the degree of physical separation between two ormore SNP sites necessary for LD to occur can differ between differentregions of the genome.

For diagnostic purposes and similar uses, if a particular SNP site isfound to be useful for, for example, predicting an individual'ssusceptibility to an acute coronary event or an individual's response tostatin treatment, then the skilled artisan would recognize that otherSNP sites which are in LD with this SNP site would also be useful forpredicting an individual's response to statin treatment. Various degreesof LD can be encountered between two or more SNPs with the result beingthat some SNPs are more closely associated (i.e., in stronger LD) thanothers. Furthermore, the physical distance over which LD extends along achromosome differs between different regions of the genome, andtherefore the degree of physical separation between two or more SNPsites necessary for LD to occur can differ between different regions ofthe genome. Thus, polymorphisms (e.g., SNPs and/or haplotypes) that arenot the actual disease-causing (causative) polymorphisms, but are in LDwith such causative polymorphisms, are also useful. In such instances,the genotype of the polymorphism(s) that is/are in LD with the causativepolymorphism is predictive of the genotype of the causative polymorphismand, consequently, predictive of the phenotype (e.g.,responder/non-responder to statin treatment) that is influenced by thecausative SNP(s). Therefore, polymorphic markers that are in LD withcausative polymorphisms are useful as diagnostic markers, and areparticularly useful when the actual causative polymorphism(s) is/areunknown.

Examples of polymorphisms that can be in LD with one or more causativepolymorphisms (and/or in LD with one or more polymorphisms that have asignificant statistical association with a condition) and thereforeuseful for diagnosing the same condition that the causative/associatedSNP(s) is used to diagnose, include, for example, other SNPs in the samegene, protein-coding, or mRNA transcript-coding region as thecausative/associated SNP, other SNPs in the same exon or same intron asthe causative/associated SNP, other SNPs in the same haplotype block asthe causative/associated SNP, other SNPs in the same intergenic regionas the causative/associated SNP, SNPs that are outside but near a gene(e.g., within 6 kb on either side, 5′ or 3′, of a gene boundary) thatharbors a causative/associated SNP, etc. Such useful LD SNPs can beselected from among the SNPs disclosed in Tables 1-2, for example.

Linkage disequilibrium in the human genome is reviewed in: Wall et al.,“Haplotype blocks and linkage disequilibrium in the human genome”, NatRev Genet. 2003 August; 4(8):587-97; Garner et al., “On selectingmarkers for association studies: patterns of linkage disequilibriumbetween two and three diallelic loci”, Genet Epidemiol. 2003 January;24(1):57-67; Ardlie et al., “Patterns of linkage disequilibrium in thehuman genome”, Nat Rev Genet. 2002 April; 3(4):299-309 (erratum in NatRev Genet 2002 July; 3(7):566); and Remm et al., “High-densitygenotyping and linkage disequilibrium in the human genome usingchromosome 22 as a model”; Curr Opin Chem Biol. 2002 February;6(1):24-30.

The contribution or association of particular SNPs and/or SNP haplotypeswith disease phenotypes, such as susceptibility to acute coronary eventsor responsiveness to statin treatment, enables the SNPs of the presentinvention to be used to develop superior diagnostic tests capable ofidentifying individuals who express a detectable trait, such aspredisposition to acute coronary events or responder/non-responder tostatin treatment, as the result of a specific genotype, or individualswhose genotype places them at an increased or decreased risk ofdeveloping a detectable trait at a subsequent time as compared toindividuals who do not have that genotype. As described herein,diagnostics may be based on a single SNP or a group of SNPs. Combineddetection of a plurality of SNPs (for example, 2, 3, 4, 5, 6, 7, 8, 9,10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 24, 25, 30, 32, 48, 50, 64,96, 100, or any other number in-between, or more, of the SNPs providedin Table 1 and/or Table 2) typically increases the probability of anaccurate diagnosis. For example, the presence of a single SNP known tocorrelate with response to statin treatment might indicate a probabilityof 20% that an individual will respond to statin treatment, whereasdetection of five SNPs, each of which correlates with response to statintreatment, might indicate a probability of 80% that an individual willrespond to statin treatment. To further increase the accuracy ofdiagnosis or predisposition screening, analysis of the SNPs of thepresent invention can be combined with that of other polymorphisms orother risk factors that correlate with disease risk and response tostatin treatment, such as family history.

It will, of course, be understood by practitioners skilled in thetreatment or diagnosis of cardiovascular disorders that the presentinvention generally does not intend to provide an absoluteidentification of individuals who will or will not experience an acutecoronary event or develop another cardiovascular disorder, or thoseindividuals who will or will not respond to statin treatment ofcardiovascular disorders, but rather to indicate a certain increased (ordecreased) degree or likelihood of developing an acute coronary event orresponding to statin treatment based on statistically significantassociation results. However, this information is extremely valuable asit can, for example, indicate that an individual having a cardiovasculardisorder should follow a particular statin-based treatment regimen, orshould follow an alternative treatment regimen that does not involvestatin. This information can also be used to initiate preventivetreatments or to allow an individual carrying one or more significantSNPs or SNP haplotypes to foresee warning signs such as minor clinicalsymptoms of cardiovascular disease, or to have regularly scheduledphysical exams to monitor for cardiovascular disorders in order toidentify and begin treatment of the disorder at an early stage.Particularly with diseases that are extremely debilitating or fatal ifnot treated on time, the knowledge of a potential predisposition to thedisease or likelihood of responding to available treatments, even ifthis predisposition or likelihood is not absolute, would likelycontribute in a very significant manner to treatment efficacy.

The diagnostic techniques of the present invention may employ a varietyof methodologies to determine whether a test subject has a SNP or a SNPpattern associated with an increased or decreased risk of developing adetectable trait or whether the individual suffers from a detectabletrait as a result of a particular polymorphism/mutation, including, forexample, methods which enable the analysis of individual chromosomes forhaplotyping, family studies, single sperm DNA analysis, or somatichybrids. The trait analyzed using the diagnostics of the invention maybe any detectable trait that is commonly observed in cardiovasculardisorders or during the course of statin treatment.

Another aspect of the present invention relates to a method ofdetermining whether an individual is at risk (or less at risk) ofdeveloping one or more traits or whether an individual expresses one ormore traits as a consequence of possessing a particular trait-causing ortrait-influencing allele. These methods generally involve obtaining anucleic acid sample from an individual and assaying the nucleic acidsample to determine which nucleotide(s) is/are present at one or moreSNP positions, wherein the assayed nucleotide(s) is/are indicative of anincreased or decreased risk of developing the trait or indicative thatthe individual expresses the trait as a result of possessing aparticular trait-causing or trait-influencing allele.

In another embodiment, the SNP detection reagents of the presentinvention are used to determine whether an individual has one or moreSNP allele(s) affecting the level (e.g., the concentration of mRNA orprotein in a sample, etc.) or pattern (e.g., the kinetics of expression,rate of decomposition, stability profile, Km, Vmax, etc.) of geneexpression (collectively, the “gene response” of a cell or bodilyfluid). Such a determination can be accomplished by screening for mRNAor protein expression (e.g., by using nucleic acid arrays, RT-PCR,TaqMan assays, or mass spectrometry), identifying genes having alteredexpression in an individual, genotyping SNPs disclosed in Table 1 and/orTable 2 that could affect the expression of the genes having alteredexpression (e.g., SNPs that are in and/or around the gene(s) havingaltered expression, SNPs in regulatory/control regions, SNPs in and/oraround other genes that are involved in pathways that could affect theexpression of the gene(s) having altered expression, or all SNPs couldbe genotyped), and correlating SNP genotypes with altered geneexpression. In this manner, specific SNP alleles at particular SNP sitescan be identified that affect gene expression.

Pharmacogenomics and Therapeutics/Drug Development

The present invention provides methods for assessing thepharmacogenomics of a subject harboring particular SNP alleles orhaplotypes to a particular therapeutic agent or pharmaceutical compound,or to a class of such compounds. Pharmacogenomics deals with the roleswhich clinically significant hereditary variations (e.g., SNPs) play inthe response to drugs due to altered drug disposition and/or abnormalaction in affected persons. See, e.g., Roses, Nature 405, 857-865(2000); Gould Rothberg, Nature Biotechnology 19, 209-211(2001);Eichelbaum, Clin. Exp. Pharmacol. Physiol. 23(10-11):983-985 (1996); andLinder, Clin. Chem. 43(2):254-266 (1997). The clinical outcomes of thesevariations can result in severe toxicity of therapeutic drugs in certainindividuals or therapeutic failure of drugs in certain individuals as aresult of individual variation in metabolism. Thus, the SNP genotype ofan individual can determine the way a therapeutic compound acts on thebody or the way the body metabolizes the compound. For example, SNPs indrug metabolizing enzymes can affect the activity of these enzymes,which in turn can affect both the intensity and duration of drug action,as well as drug metabolism and clearance.

The discovery of SNPs in drug metabolizing enzymes, drug transporters,proteins for pharmaceutical agents, and other drug targets has explainedwhy some patients do not obtain the expected drug effects, show anexaggerated drug effect, or experience serious toxicity from standarddrug dosages. SNPs can be expressed in the phenotype of the extensivemetabolizer and in the phenotype of the poor metabolizer. Accordingly,SNPs may lead to allelic variants of a protein in which one or more ofthe protein functions in one population are different from those inanother population. SNPs and the encoded variant peptides thus providetargets to ascertain a genetic predisposition that can affect treatmentmodality. For example, in a ligand-based treatment, SNPs may give riseto amino terminal extracellular domains and/or other ligand-bindingregions of a receptor that are more or less active in ligand binding,thereby affecting subsequent protein activation. Accordingly, liganddosage would necessarily be modified to maximize the therapeutic effectwithin a given population containing particular SNP alleles orhaplotypes.

As an alternative to genotyping, specific variant proteins containingvariant amino acid sequences encoded by alternative SNP alleles could beidentified. Thus, pharmacogenomic characterization of an individualpermits the selection of effective compounds and effective dosages ofsuch compounds for prophylactic or therapeutic uses based on theindividual's SNP genotype, thereby enhancing and optimizing theeffectiveness of the therapy. Furthermore, the production of recombinantcells and transgenic animals containing particular SNPs/haplotypes alloweffective clinical design and testing of treatment compounds and dosageregimens. For example, transgenic animals can be produced that differonly in specific SNP alleles in a gene that is orthologous to a humandisease susceptibility gene.

Pharmacogenomic uses of the SNPs of the present invention provideseveral significant advantages for patient care, particularly inpredicting an individual's predisposition to acute coronary events andother cardiovascular disorders and in predicting an individual'sresponsiveness to the use of statin for treating cardiovascular disease.Pharmacogenomic characterization of an individual, based on anindividual's SNP genotype, can identify those individuals unlikely torespond to treatment with a particular medication and thereby allowsphysicians to avoid prescribing the ineffective medication to thoseindividuals. On the other hand, SNP genotyping of an individual mayenable physicians to select the appropriate medication and dosageregimen that will be most effective based on an individual's SNPgenotype. This information increases a physician's confidence inprescribing medications and motivates patients to comply with their drugregimens. Furthermore, pharmacogenomics may identify patientspredisposed to toxicity and adverse reactions to particular drugs ordrug dosages. Adverse drug reactions lead to more than 100,000 avoidabledeaths per year in the United States alone and therefore represent asignificant cause of hospitalization and death, as well as a significanteconomic burden on the healthcare system (Pfost et. al., Trends inBiotechnology, August 2000.). Thus, pharmacogenomics based on the SNPsdisclosed herein has the potential to both save lives and reducehealthcare costs substantially.

Pharmacogenomics in general is discussed further in Rose et al.,“Pharmacogenetic analysis of clinically relevant genetic polymorphisms”,Methods Mol Med. 2003; 85:225-37. Pharmacogenomics as it relates toAlzheimer's disease and other neurodegenerative disorders is discussedin Cacabelos, “Pharmacogenomics for the treatment of dementia”, Ann Med.2002; 34(5):357-79, Maimone et al., “Pharmacogenomics ofneurodegenerative diseases”, Eur J Pharmacol. 2001 Feb. 9; 413(1):11-29,and Poirier, “Apolipoprotein E: a pharmacogenetic target for thetreatment of Alzheimer's disease”, Mol Diagn. 1999 December;4(4):335-41. Pharmacogenomics as it relates to cardiovascular disordersis discussed in Siest et al., “Pharmacogenomics of drugs affecting thecardiovascular system”, Clin Chem Lab Med. 2003 April; 41(4):590-9,Mukherjee et al., “Pharmacogenomics in cardiovascular diseases”, ProgCardiovasc Dis. 2002 May-June; 44(6):479-98, and Mooser et al.,“Cardiovascular pharmacogenetics in the SNP era”, J Thromb Haemost. 2003July; 1(7):1398-402. Pharmacogenomics as it relates to cancer isdiscussed in McLeod et al., “Cancer pharmacogenomics: SNPs, chips, andthe individual patient”, Cancer Invest. 2003; 21(4):630-40 and Watterset al., “Cancer pharmacogenomics: current and future applications”,Biochim Biophys Acta. 2003 Mar. 17; 1603(2):99-111.

The SNPs of the present invention also can be used to identify noveltherapeutic targets for cardiovascular disorders. For example, genescontaining the disease-associated variants (“variant genes”) or theirproducts, as well as genes or their products that are directly orindirectly regulated by or interacting with these variant genes or theirproducts, can be targeted for the development of therapeutics that, forexample, treat the disease or prevent or delay disease onset. Thetherapeutics may be composed of, for example, small molecules, proteins,protein fragments or peptides, antibodies, nucleic acids, or theirderivatives or mimetics which modulate the functions or levels of thetarget genes or gene products.

The SNP-containing nucleic acid molecules disclosed herein, and theircomplementary nucleic acid molecules, may be used as antisenseconstructs to control gene expression in cells, tissues, and organisms.Antisense technology is well established in the art and extensivelyreviewed in Antisense Drug Technology: Principles, Strategies, andApplications, Crooke (ed.), Marcel Dekker, Inc.: New York (2001). Anantisense nucleic acid molecule is generally designed to becomplementary to a region of mRNA expressed by a gene so that theantisense molecule hybridizes to the mRNA and thereby blocks translationof mRNA into protein. Various classes of antisense oligonucleotides areused in the art, two of which are cleavers and blockers. Cleavers, bybinding to target RNAs, activate intracellular nucleases (e.g., RNaseHor RNase L) that cleave the target RNA. Blockers, which also bind totarget RNAs, inhibit protein translation through steric hindrance ofribosomes. Exemplary blockers include peptide nucleic acids,morpholinos, locked nucleic acids, and methylphosphonates (see, e.g.,Thompson, Drug Discovery Today, 7 (17): 912-917 (2002)). Antisenseoligonucleotides are directly useful as therapeutic agents, and are alsouseful for determining and validating gene function (e.g., in geneknock-out or knock-down experiments).

Antisense technology is further reviewed in: Lavery et al., “Antisenseand RNAi: powerful tools in drug target discovery and validation”, CurrOpin Drug Discov Devel. 2003 July; 6(4):561-9; Stephens et al.,“Antisense oligonucleotide therapy in cancer”, Curr Opin Mol Ther. 2003April; 5(2):118-22; Kurreck, “Antisense technologies. Improvementthrough novel chemical modifications”, Eur J Biochem. 2003 April;270(8):1628-44; Dias et al., “Antisense oligonucleotides: basic conceptsand mechanisms”, Mol Cancer Ther. 2002 March; 1(5):347-55; Chen,“Clinical development of antisense oligonucleotides as anti-cancertherapeutics”, Methods Mol Med. 2003; 75:621-36; Wang et al., “Antisenseanticancer oligonucleotide therapeutics”, Curr Cancer Drug Targets. 2001November; 1(3):177-96; and Bennett, “Efficiency of antisenseoligonucleotide drug discovery”, Antisense Nucleic Acid Drug Dev. 2002June; 12(3):215-24.

The SNPs of the present invention are particularly useful for designingantisense reagents that are specific for particular nucleic acidvariants. Based on the SNP information disclosed herein, antisenseoligonucleotides can be produced that specifically target mRNA moleculesthat contain one or more particular SNP nucleotides. In this manner,expression of mRNA molecules that contain one or more undesiredpolymorphisms (e.g., SNP nucleotides that lead to a defective proteinsuch as an amino acid substitution in a catalytic domain) can beinhibited or completely blocked. Thus, antisense oligonucleotides can beused to specifically bind a particular polymorphic form (e.g., a SNPallele that encodes a defective protein), thereby inhibiting translationof this form, but which do not bind an alternative polymorphic form(e.g., an alternative SNP nucleotide that encodes a protein havingnormal function).

Antisense molecules can be used to inactivate mRNA in order to inhibitgene expression and production of defective proteins. Accordingly, thesemolecules can be used to treat a disorder, such as a cardiovasculardisorder, characterized by abnormal or undesired gene expression orexpression of certain defective proteins. This technique can involvecleavage by means of ribozymes containing nucleotide sequencescomplementary to one or more regions in the mRNA that attenuate theability of the mRNA to be translated. Possible mRNA regions include, forexample, protein-coding regions and particularly protein-coding regionscorresponding to catalytic activities, substrate/ligand binding, orother functional activities of a protein.

The SNPs of the present invention are also useful for designing RNAinterference reagents that specifically target nucleic acid moleculeshaving particular SNP variants. RNA interference (RNAi), also referredto as gene silencing, is based on using double-stranded RNA (dsRNA)molecules to turn genes off. When introduced into a cell, dsRNAs areprocessed by the cell into short fragments (generally about 21, 22, or23 nucleotides in length) known as small interfering RNAs (siRNAs) whichthe cell uses in a sequence-specific manner to recognize and destroycomplementary RNAs (Thompson, Drug Discovery Today, 7 (17): 912-917(2002)). Accordingly, an aspect of the present invention specificallycontemplates isolated nucleic acid molecules that are about 18-26nucleotides in length, preferably 19-25 nucleotides in length, and morepreferably 20, 21, 22, or 23 nucleotides in length, and the use of thesenucleic acid molecules for RNAi. Because RNAi molecules, includingsiRNAs, act in a sequence-specific manner, the SNPs of the presentinvention can be used to design RNAi reagents that recognize and destroynucleic acid molecules having specific SNP alleles/nucleotides (such asdeleterious alleles that lead to the production of defective proteins),while not affecting nucleic acid molecules having alternative SNPalleles (such as alleles that encode proteins having normal function).As with antisense reagents, RNAi reagents may be directly useful astherapeutic agents (e.g., for turning off defective, disease-causinggenes), and are also useful for characterizing and validating genefunction (e.g., in gene knock-out or knock-down experiments).

The following references provide a further review of RNAi: Reynolds etal., “Rational siRNA design for RNA interference”, Nat Biotechnol. 2004March; 22(3):326-30. Epub 2004 Feb. 1; Chi et al., “Genomewide view ofgene silencing by small interfering RNAs”, PNAS 100(11):6343-6346, 2003;Vickers et al., “Efficient Reduction of Target RNAs by Small InterferingRNA and RNase H-dependent Antisense Agents”, J. Biol. Chem. 278:7108-7118, 2003; Agami, “RNAi and related mechanisms and their potentialuse for therapy”, Curr Opin Chem Biol. 2002 December; 6(6):829-34;Lavery et al., “Antisense and RNAi: powerful tools in drug targetdiscovery and validation”, Curr Opin Drug Discov Devel. 2003 July;6(4):561-9; Shi, “Mammalian RNAi for the masses”, Trends Genet 2003January; 19(1):9-12), Shuey et al., “RNAi: gene-silencing in therapeuticintervention”, Drug Discovery Today 2002 October; 7(20):1040-1046;McManus et al., Nat Rev Genet 2002 October; 3(10):737-47; Xia et al.,Nat Biotechnol 2002 October; 20(10):1006-10; Plasterk et al., Curr OpinGenet Dev 2000 October; 10(5):562-7; Bosher et al., Nat Cell Biol 2000February; 2(2):E31-6; and Hunter, Curr Biol 1999 Jun. 17; 9(12):R440-2).

A subject suffering from a pathological condition, such as acardiovascular disorder, ascribed to a SNP may be treated so as tocorrect the genetic defect (see Kren et al., Proc. Natl. Acad. Sci. USA96:10349-10354 (1999)). Such a subject can be identified by any methodthat can detect the polymorphism in a biological sample drawn from thesubject. Such a genetic defect may be permanently corrected byadministering to such a subject a nucleic acid fragment incorporating arepair sequence that supplies the normal/wild-type nucleotide at theposition of the SNP. This site-specific repair sequence can encompass anRNA/DNA oligonucleotide that operates to promote endogenous repair of asubject's genomic DNA. The site-specific repair sequence is administeredin an appropriate vehicle, such as a complex with polyethylenimine,encapsulated in anionic liposomes, a viral vector such as an adenovirus,or other pharmaceutical composition that promotes intracellular uptakeof the administered nucleic acid. A genetic defect leading to an inbornpathology may then be overcome, as the chimeric oligonucleotides induceincorporation of the normal sequence into the subject's genome. Uponincorporation, the normal gene product is expressed, and the replacementis propagated, thereby engendering a permanent repair and therapeuticenhancement of the clinical condition of the subject.

In cases in which a cSNP results in a variant protein that is ascribedto be the cause of, or a contributing factor to, a pathologicalcondition, a method of treating such a condition can includeadministering to a subject experiencing the pathology thewild-type/normal cognate of the variant protein. Once administered in aneffective dosing regimen, the wild-type cognate provides complementationor remediation of the pathological condition.

The invention further provides a method for identifying a compound oragent that can be used to treat cardiovascular disorders. The SNPsdisclosed herein are useful as targets for the identification and/ordevelopment of therapeutic agents. A method for identifying atherapeutic agent or compound typically includes assaying the ability ofthe agent or compound to modulate the activity and/or expression of aSNP-containing nucleic acid or the encoded product and thus identifyingan agent or a compound that can be used to treat a disordercharacterized by undesired activity or expression of the SNP-containingnucleic acid or the encoded product. The assays can be performed incell-based and cell-free systems. Cell-based assays can include cellsnaturally expressing the nucleic acid molecules of interest orrecombinant cells genetically engineered to express certain nucleic acidmolecules.

Variant gene expression in a patient having a cardiovascular disorder orundergoing statin treatment can include, for example, either expressionof a SNP-containing nucleic acid sequence (for instance, a gene thatcontains a SNP can be transcribed into an mRNA transcript moleculecontaining the SNP, which can in turn be translated into a variantprotein) or altered expression of a normal/wild-type nucleic acidsequence due to one or more SNPs (for instance, a regulatory/controlregion can contain a SNP that affects the level or pattern of expressionof a normal transcript).

Assays for variant gene expression can involve direct assays of nucleicacid levels (e.g., mRNA levels), expressed protein levels, or ofcollateral compounds involved in a signal pathway. Further, theexpression of genes that are up- or down-regulated in response to thesignal pathway can also be assayed. In this embodiment, the regulatoryregions of these genes can be operably linked to a reporter gene such asluciferase.

Modulators of variant gene expression can be identified in a methodwherein, for example, a cell is contacted with a candidatecompound/agent and the expression of mRNA determined. The level ofexpression of mRNA in the presence of the candidate compound is comparedto the level of expression of mRNA in the absence of the candidatecompound. The candidate compound can then be identified as a modulatorof variant gene expression based on this comparison and be used to treata disorder such as a cardiovascular disorder that is characterized byvariant gene expression (e.g., either expression of a SNP-containingnucleic acid or altered expression of a normal/wild-type nucleic acidmolecule due to one or more SNPs that affect expression of the nucleicacid molecule) due to one or more SNPs of the present invention. Whenexpression of mRNA is statistically significantly greater in thepresence of the candidate compound than in its absence, the candidatecompound is identified as a stimulator of nucleic acid expression. Whennucleic acid expression is statistically significantly less in thepresence of the candidate compound than in its absence, the candidatecompound is identified as an inhibitor of nucleic acid expression.

The invention further provides methods of treatment, with the SNP orassociated nucleic acid domain (e.g., catalytic domain,ligand/substrate-binding domain, regulatory/control region, etc.) orgene, or the encoded mRNA transcript, as a target, using a compoundidentified through drug screening as a gene modulator to modulatevariant nucleic acid expression. Modulation can include eitherup-regulation (i.e., activation or agonization) or down-regulation(i.e., suppression or antagonization) of nucleic acid expression.

Expression of mRNA transcripts and encoded proteins, either wild type orvariant, may be altered in individuals with a particular SNP allele in aregulatory/control element, such as a promoter or transcription factorbinding domain, that regulates expression. In this situation, methods oftreatment and compounds can be identified, as discussed herein, thatregulate or overcome the variant regulatory/control element, therebygenerating normal, or healthy, expression levels of either the wild typeor variant protein.

The SNP-containing nucleic acid molecules of the present invention arealso useful for monitoring the effectiveness of modulating compounds onthe expression or activity of a variant gene, or encoded product, inclinical trials or in a treatment regimen. Thus, the gene expressionpattern can serve as an indicator for the continuing effectiveness oftreatment with the compound, particularly with compounds to which apatient can develop resistance, as well as an indicator for toxicities.The gene expression pattern can also serve as a marker indicative of aphysiological response of the affected cells to the compound.Accordingly, such monitoring would allow either increased administrationof the compound or the administration of alternative compounds to whichthe patient has not become resistant. Similarly, if the level of nucleicacid expression falls below a desirable level, administration of thecompound could be commensurately decreased.

In another aspect of the present invention, there is provided apharmaceutical pack comprising a therapeutic agent (e.g., a smallmolecule drug, antibody, peptide, antisense or RNAi nucleic acidmolecule, etc.) and a set of instructions for administration of thetherapeutic agent to humans diagnostically tested for one or more SNPsor SNP haplotypes provided by the present invention.

The SNPs/haplotypes of the present invention are also useful forimproving many different aspects of the drug development process. Forinstance, an aspect of the present invention includes selectingindividuals for clinical trials based on their SNP genotype. Forexample, individuals with SNP genotypes that indicate that they arelikely to positively respond to a drug can be included in the trials,whereas those individuals whose SNP genotypes indicate that they areless likely to or would not respond to the drug, or who are at risk forsuffering toxic effects or other adverse reactions, can be excluded fromthe clinical trials. This not only can improve the safety of clinicaltrials, but also can enhance the chances that the trial will demonstratestatistically significant efficacy. Furthermore, the SNPs of the presentinvention may explain why certain previously developed drugs performedpoorly in clinical trials and may help identify a subset of thepopulation that would benefit from a drug that had previously performedpoorly in clinical trials, thereby “rescuing” previously developeddrugs, and enabling the drug to be made available to a particularpatient population that can benefit from it.

SNPs have many important uses in drug discovery, screening, anddevelopment. A high probability exists that, for any gene/proteinselected as a potential drug target, variants of that gene/protein willexist in a patient population. Thus, determining the impact ofgene/protein variants on the selection and delivery of a therapeuticagent should be an integral aspect of the drug discovery and developmentprocess. (Jazwinska, A Trends Guide to Genetic Variation and GenomicMedicine, 2002 March; S30-S36).

Knowledge of variants (e.g., SNPs and any corresponding amino acidpolymorphisms) of a particular therapeutic target (e.g., a gene, mRNAtranscript, or protein) enables parallel screening of the variants inorder to identify therapeutic candidates (e.g., small moleculecompounds, antibodies, antisense or RNAi nucleic acid compounds, etc.)that demonstrate efficacy across variants (Rothberg, Nat Biotechnol 2001March; 19(3):209-11). Such therapeutic candidates would be expected toshow equal efficacy across a larger segment of the patient population,thereby leading to a larger potential market for the therapeuticcandidate.

Furthermore, identifying variants of a potential therapeutic targetenables the most common form of the target to be used for selection oftherapeutic candidates, thereby helping to ensure that the experimentalactivity that is observed for the selected candidates reflects the realactivity expected in the largest proportion of a patient population(Jazwinska, A Trends Guide to Genetic Variation and Genomic Medicine,2002 March; S30-S36).

Additionally, screening therapeutic candidates against all knownvariants of a target can enable the early identification of potentialtoxicities and adverse reactions relating to particular variants. Forexample, variability in drug absorption, distribution, metabolism andexcretion (ADME) caused by, for example, SNPs in therapeutic targets ordrug metabolizing genes, can be identified, and this information can beutilized during the drug development process to minimize variability indrug disposition and develop therapeutic agents that are safer across awider range of a patient population. The SNPs of the present invention,including the variant proteins and encoding polymorphic nucleic acidmolecules provided in Tables 1-2, are useful in conjunction with avariety of toxicology methods established in the art, such as those setforth in Current Protocols in Toxicology, John Wiley & Sons, Inc., N.Y.

Furthermore, therapeutic agents that target any art-known proteins (ornucleic acid molecules, either RNA or DNA) may cross-react with thevariant proteins (or polymorphic nucleic acid molecules) disclosed inTable 1, thereby significantly affecting the pharmacokinetic propertiesof the drug. Consequently, the protein variants and the SNP-containingnucleic acid molecules disclosed in Tables 1-2 are useful in developing,screening, and evaluating therapeutic agents that target correspondingart-known protein forms (or nucleic acid molecules). Additionally, asdiscussed above, knowledge of all polymorphic forms of a particular drugtarget enables the design of therapeutic agents that are effectiveagainst most or all such polymorphic forms of the drug target.

Pharmaceutical Compositions and Administration Thereof

Any of the cardiovascular disease and/or statin response-associatedproteins, and encoding nucleic acid molecules, disclosed herein can beused as therapeutic targets (or directly used themselves as therapeuticcompounds) for treating cardiovascular disorders and relatedpathologies, and the present disclosure enables therapeutic compounds(e.g., small molecules, antibodies, therapeutic proteins, RNAi andantisense molecules, etc.) to be developed that target (or are comprisedof) any of these therapeutic targets.

In general, a therapeutic compound will be administered in atherapeutically effective amount by any of the accepted modes ofadministration for agents that serve similar utilities. The actualamount of the therapeutic compound of this invention, i.e., the activeingredient, will depend upon numerous factors such as the severity ofthe disease to be treated, the age and relative health of the subject,the potency of the compound used, the route and form of administration,and other factors.

Therapeutically effective amounts of therapeutic compounds may rangefrom, for example, approximately 0.01-50 mg per kilogram body weight ofthe recipient per day; preferably about 0.1-20 mg/kg/day. Thus, as anexample, for administration to a 70 kg person, the dosage range wouldmost preferably be about 7 mg to 1.4 g per day.

In general, therapeutic compounds will be administered as pharmaceuticalcompositions by any one of the following routes: oral, systemic (e.g.,transdermal, intranasal, or by suppository), or parenteral (e.g.,intramuscular, intravenous, or subcutaneous) administration. Thepreferred manner of administration is oral or parenteral using aconvenient daily dosage regimen, which can be adjusted according to thedegree of affliction. Oral compositions can take the form of tablets,pills, capsules, semisolids, powders, sustained release formulations,solutions, suspensions, elixirs, aerosols, or any other appropriatecompositions.

The choice of formulation depends on various factors such as the mode ofdrug administration (e.g., for oral administration, formulations in theform of tablets, pills, or capsules are preferred) and thebioavailability of the drug substance. Recently, pharmaceuticalformulations have been developed especially for drugs that show poorbioavailability based upon the principle that bioavailability can beincreased by increasing the surface area, i.e., decreasing particlesize. For example, U.S. Pat. No. 4,107,288 describes a pharmaceuticalformulation having particles in the size range from 10 to 1,000 nm inwhich the active material is supported on a cross-linked matrix ofmacromolecules. U.S. Pat. No. 5,145,684 describes the production of apharmaceutical formulation in which the drug substance is pulverized tonanoparticles (average particle size of 400 nm) in the presence of asurface modifier and then dispersed in a liquid medium to give apharmaceutical formulation that exhibits remarkably highbioavailability.

Pharmaceutical compositions are comprised of, in general, a therapeuticcompound in combination with at least one pharmaceutically acceptableexcipient. Acceptable excipients are non-toxic, aid administration, anddo not adversely affect the therapeutic benefit of the therapeuticcompound. Such excipients may be any solid, liquid, semi-solid or, inthe case of an aerosol composition, gaseous excipient that is generallyavailable to one skilled in the art.

Solid pharmaceutical excipients include starch, cellulose, talc,glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk, silicagel, magnesium stearate, sodium stearate, glycerol monostearate, sodiumchloride, dried skim milk and the like. Liquid and semisolid excipientsmay be selected from glycerol, propylene glycol, water, ethanol andvarious oils, including those of petroleum, animal, vegetable orsynthetic origin, e.g., peanut oil, soybean oil, mineral oil, sesameoil, etc. Preferred liquid carriers, particularly for injectablesolutions, include water, saline, aqueous dextrose, and glycols.

Compressed gases may be used to disperse a compound of this invention inaerosol form. Inert gases suitable for this purpose are nitrogen, carbondioxide, etc.

Other suitable pharmaceutical excipients and their formulations aredescribed in Remington's Pharmaceutical Sciences, edited by E. W. Martin(Mack Publishing Company, 18th ed., 1990).

The amount of the therapeutic compound in a formulation can vary withinthe full range employed by those skilled in the art. Typically, theformulation will contain, on a weight percent (wt %) basis, from about0.01-99.99 wt % of the therapeutic compound based on the totalformulation, with the balance being one or more suitable pharmaceuticalexcipients. Preferably, the compound is present at a level of about 1-80wt %.

Therapeutic compounds can be administered alone or in combination withother therapeutic compounds or in combination with one or more otheractive ingredient(s). For example, an inhibitor or stimulator of acardiovascular disorder-associated protein can be administered incombination with another agent that inhibits or stimulates the activityof the same or a different cardiovascular disorder-associated protein tothereby counteract the affects of a cardiovascular disorder.

For further information regarding pharmacology, see Current Protocols inPharmacology, John Wiley & Sons, Inc., N.Y.

Human Identification Applications

In addition to their diagnostic and therapeutic uses in cardiovasculardisorders and statin treatment of cardiovascular disorders, the SNPsprovided by the present invention are also useful as humanidentification markers for such applications as forensics, paternitytesting, and biometrics (see, e.g., Gill, “An assessment of the utilityof single nucleotide polymorphisms (SNPs) for forensic purposes”, Int JLegal Med. 2001; 114(4-5):204-10). Genetic variations in the nucleicacid sequences between individuals can be used as genetic markers toidentify individuals and to associate a biological sample with anindividual. Determination of which nucleotides occupy a set of SNPpositions in an individual identifies a set of SNP markers thatdistinguishes the individual. The more SNP positions that are analyzed,the lower the probability that the set of SNPs in one individual is thesame as that in an unrelated individual. Preferably, if multiple sitesare analyzed, the sites are unlinked (i.e., inherited independently).Thus, preferred sets of SNPs can be selected from among the SNPsdisclosed herein, which may include SNPs on different chromosomes, SNPson different chromosome arms, and/or SNPs that are dispersed oversubstantial distances along the same chromosome arm.

Furthermore, among the SNPs disclosed herein, preferred SNPs for use incertain forensic/human identification applications include SNPs locatedat degenerate codon positions (i.e., the third position in certaincodons which can be one of two or more alternative nucleotides and stillencode the same amino acid), since these SNPs do not affect the encodedprotein. SNPs that do not affect the encoded protein are expected to beunder less selective pressure and are therefore expected to be morepolymorphic in a population, which is typically an advantage forforensic/human identification applications. However, for certainforensics/human identification applications, such as predictingphenotypic characteristics (e.g., inferring ancestry or inferring one ormore physical characteristics of an individual) from a DNA sample, itmay be desirable to utilize SNPs that affect the encoded protein.

For many of the SNPs disclosed in Tables 1-2 (which are identified as“Applera” SNP source), Tables 1-2 provide SNP allele frequenciesobtained by re-sequencing the DNA of chromosomes from 39 individuals(Tables 1-2 also provide allele frequency information for “Celera”source SNPs and, where available, public SNPs from dbEST, HGBASE, and/orHGMD). The allele frequencies provided in Tables 1-2 enable these SNPsto be readily used for human identification applications. Although anySNP disclosed in Table 1 and/or Table 2 could be used for humanidentification, the closer that the frequency of the minor allele at aparticular SNP site is to 50%, the greater the ability of that SNP todiscriminate between different individuals in a population since itbecomes increasingly likely that two randomly selected individuals wouldhave different alleles at that SNP site. Using the SNP allelefrequencies provided in Tables 1-2, one of ordinary skill in the artcould readily select a subset of SNPs for which the frequency of theminor allele is, for example, at least 1%, 2%, 5%, 10%, 20%, 25%, 30%,40%, 45%, or 50%, or any other frequency in-between. Thus, since Tables1-2 provide allele frequencies based on the re-sequencing of thechromosomes from 39 individuals, a subset of SNPs could readily beselected for human identification in which the total allele count of theminor allele at a particular SNP site is, for example, at least 1, 2, 4,8, 10, 16, 20, 24, 30, 32, 36, 38, 39, 40, or any other numberin-between.

Furthermore, Tables 1-2 also provide population group (interchangeablyreferred to herein as ethnic or racial groups) information coupled withthe extensive allele frequency information. For example, the group of 39individuals whose DNA was re-sequenced was made-up of 20 Caucasians and19 African-Americans. This population group information enables furtherrefinement of SNP selection for human identification. For example,preferred SNPs for human identification can be selected from Tables 1-2that have similar allele frequencies in both the Caucasian andAfrican-American populations; thus, for example, SNPs can be selectedthat have equally high discriminatory power in both populations.Alternatively, SNPs can be selected for which there is a statisticallysignificant difference in allele frequencies between the Caucasian andAfrican-American populations (as an extreme example, a particular allelemay be observed only in either the Caucasian or the African-Americanpopulation group but not observed in the other population group); suchSNPs are useful, for example, for predicting the race/ethnicity of anunknown perpetrator from a biological sample such as a hair or bloodstain recovered at a crime scene. For a discussion of using SNPs topredict ancestry from a DNA sample, including statistical methods, seeFrudakis et al., “A Classifier for the SNP-Based Inference of Ancestry”,Journal of Forensic Sciences 2003; 48(4):771-782.

SNPs have numerous advantages over other types of polymorphic markers,such as short tandem repeats (STRs). For example, SNPs can be easilyscored and are amenable to automation, making SNPs the markers of choicefor large-scale forensic databases. SNPs are found in much greaterabundance throughout the genome than repeat polymorphisms. Populationfrequencies of two polymorphic forms can usually be determined withgreater accuracy than those of multiple polymorphic forms atmulti-allelic loci. SNPs are mutationaly more stable than repeatpolymorphisms. SNPs are not susceptible to artefacts such as stutterbands that can hinder analysis. Stutter bands are frequently encounteredwhen analyzing repeat polymorphisms, and are particularly troublesomewhen analyzing samples such as crime scene samples that may containmixtures of DNA from multiple sources. Another significant advantage ofSNP markers over STR markers is the much shorter length of nucleic acidneeded to score a SNP. For example, STR markers are generally severalhundred base pairs in length. A SNP, on the other hand, comprises asingle nucleotide, and generally a short conserved region on either sideof the SNP position for primer and/or probe binding. This makes SNPsmore amenable to typing in highly degraded or aged biological samplesthat are frequently encountered in forensic casework in which DNA may befragmented into short pieces.

SNPs also are not subject to microvariant and “off-ladder” allelesfrequently encountered when analyzing STR loci. Microvariants aredeletions or insertions within a repeat unit that change the size of theamplified DNA product so that the amplified product does not migrate atthe same rate as reference alleles with normal sized repeat units. Whenseparated by size, such as by electrophoresis on a polyacrylamide gel,microvariants do not align with a reference allelic ladder of standardsized repeat units, but rather migrate between the reference alleles.The reference allelic ladder is used for precise sizing of alleles forallele classification; therefore alleles that do not align with thereference allelic ladder lead to substantial analysis problems.Furthermore, when analyzing multi-allelic repeat polymorphisms,occasionally an allele is found that consists of more or less repeatunits than has been previously seen in the population, or more or lessrepeat alleles than are included in a reference allelic ladder. Thesealleles will migrate outside the size range of known alleles in areference allelic ladder, and therefore are referred to as “off-ladder”alleles. In extreme cases, the allele may contain so few or so manyrepeats that it migrates well out of the range of the reference allelicladder. In this situation, the allele may not even be observed, or, withmultiplex analysis, it may migrate within or close to the size range foranother locus, further confounding analysis.

SNP analysis avoids the problems of microvariants and off-ladder allelesencountered in STR analysis. Importantly, microvariants and off-ladderalleles may provide significant problems, and may be completely missed,when using analysis methods such as oligonucleotide hybridizationarrays, which utilize oligonucleotide probes specific for certain knownalleles. Furthermore, off-ladder alleles and microvariants encounteredwith STR analysis, even when correctly typed, may lead to improperstatistical analysis, since their frequencies in the population aregenerally unknown or poorly characterized, and therefore the statisticalsignificance of a matching genotype may be questionable. All theseadvantages of SNP analysis are considerable in light of the consequencesof most DNA identification cases, which may lead to life imprisonmentfor an individual, or re-association of remains to the family of adeceased individual.

DNA can be isolated from biological samples such as blood, bone, hair,saliva, or semen, and compared with the DNA from a reference source atparticular SNP positions. Multiple SNP markers can be assayedsimultaneously in order to increase the power of discrimination and thestatistical significance of a matching genotype. For example,oligonucleotide arrays can be used to genotype a large number of SNPssimultaneously. The SNPs provided by the present invention can beassayed in combination with other polymorphic genetic markers, such asother SNPs known in the art or STRs, in order to identify an individualor to associate an individual with a particular biological sample.

Furthermore, the SNPs provided by the present invention can be genotypedfor inclusion in a database of DNA genotypes, for example, a criminalDNA databank such as the FBI's Combined DNA Index System (CODIS)database. A genotype obtained from a biological sample of unknown sourcecan then be queried against the database to find a matching genotype,with the SNPs of the present invention providing nucleotide positions atwhich to compare the known and unknown DNA sequences for identity.Accordingly, the present invention provides a database comprising novelSNPs or SNP alleles of the present invention (e.g., the database cancomprise information indicating which alleles are possessed byindividual members of a population at one or more novel SNP sites of thepresent invention), such as for use in forensics, biometrics, or otherhuman identification applications. Such a database typically comprises acomputer-based system in which the SNPs or SNP alleles of the presentinvention are recorded on a computer readable medium (see the section ofthe present specification entitled “Computer-Related Embodiments”).

The SNPs of the present invention can also be assayed for use inpaternity testing. The object of paternity testing is usually todetermine whether a male is the father of a child. In most cases, themother of the child is known and thus, the mother's contribution to thechild's genotype can be traced. Paternity testing investigates whetherthe part of the child's genotype not attributable to the mother isconsistent with that of the putative father. Paternity testing can beperformed by analyzing sets of polymorphisms in the putative father andthe child, with the SNPs of the present invention providing nucleotidepositions at which to compare the putative father's and child's DNAsequences for identity. If the set of polymorphisms in the childattributable to the father does not match the set of polymorphisms ofthe putative father, it can be concluded, barring experimental error,that the putative father is not the father of the child. If the set ofpolymorphisms in the child attributable to the father match the set ofpolymorphisms of the putative father, a statistical calculation can beperformed to determine the probability of coincidental match, and aconclusion drawn as to the likelihood that the putative father is thetrue biological father of the child.

In addition to paternity testing, SNPs are also useful for other typesof kinship testing, such as for verifying familial relationships forimmigration purposes, or for cases in which an individual alleges to berelated to a deceased individual in order to claim an inheritance fromthe deceased individual, etc. For further information regarding theutility of SNPs for paternity testing and other types of kinshiptesting, including methods for statistical analysis, see Krawczak,“Informativity assessment for biallelic single nucleotidepolymorphisms”, Electrophoresis 1999 June; 20(8):1676-81.

The use of the SNPs of the present invention for human identificationfurther extends to various authentication systems, commonly referred toas biometric systems, which typically convert physical characteristicsof humans (or other organisms) into digital data. Biometric systemsinclude various technological devices that measure such uniqueanatomical or physiological characteristics as finger, thumb, or palmprints; hand geometry; vein patterning on the back of the hand; bloodvessel patterning of the retina and color and texture of the iris;facial characteristics; voice patterns; signature and typing dynamics;and DNA. Such physiological measurements can be used to verify identityand, for example, restrict or allow access based on the identification.Examples of applications for biometrics include physical area security,computer and network security, aircraft passenger check-in and boarding,financial transactions, medical records access, government benefitdistribution, voting, law enforcement, passports, visas and immigration,prisons, various military applications, and for restricting access toexpensive or dangerous items, such as automobiles or guns (see, forexample, O'Connor, Stanford Technology Law Review and U.S. Pat. No.6,119,096).

Groups of SNPs, particularly the SNPs provided by the present invention,can be typed to uniquely identify an individual for biometricapplications such as those described above. Such SNP typing can readilybe accomplished using, for example, DNA chips/arrays. Preferably, aminimally invasive means for obtaining a DNA sample is utilized. Forexample, PCR amplification enables sufficient quantities of DNA foranalysis to be obtained from buccal swabs or fingerprints, which containDNA-containing skin cells and oils that are naturally transferred duringcontact.

Further information regarding techniques for using SNPs inforensic/human identification applications can be found in, for example,Current Protocols in Human Genetics, John Wiley & Sons, N.Y. (2002),14.1-14.7.

Variant Proteins, Antibodies,

Vectors & Host Cells, & Uses Thereof

Variant Proteins Encoded by SNP-Containing Nucleic Acid Molecules

The present invention provides SNP-containing nucleic acid molecules,many of which encode proteins having variant amino acid sequences ascompared to the art-known (i.e., wild-type) proteins. Amino acidsequences encoded by the polymorphic nucleic acid molecules of thepresent invention are provided as SEQ ID NOS:518-1034 in Table 1 and theSequence Listing. These variants will generally be referred to herein asvariant proteins/peptides/polypeptides, or polymorphicproteins/peptides/polypeptides of the present invention. The terms“protein”, “peptide”, and “polypeptide” are used herein interchangeably.

A variant protein of the present invention may be encoded by, forexample, a nonsynonymous nucleotide substitution at any one of the cSNPpositions disclosed herein. In addition, variant proteins may alsoinclude proteins whose expression, structure, and/or function is alteredby a SNP disclosed herein, such as a SNP that creates or destroys a stopcodon, a SNP that affects splicing, and a SNP in control/regulatoryelements, e.g. promoters, enhancers, or transcription factor bindingdomains.

As used herein, a protein or peptide is said to be “isolated” or“purified” when it is substantially free of cellular material orchemical precursors or other chemicals. The variant proteins of thepresent invention can be purified to homogeneity or other lower degreesof purity. The level of purification will be based on the intended use.The key feature is that the preparation allows for the desired functionof the variant protein, even if in the presence of considerable amountsof other components.

As used herein, “substantially free of cellular material” includespreparations of the variant protein having less than about 30% (by dryweight) other proteins (i.e., contaminating protein), less than about20% other proteins, less than about 10% other proteins, or less thanabout 5% other proteins. When the variant protein is recombinantlyproduced, it can also be substantially free of culture medium, i.e.,culture medium represents less than about 20% of the volume of theprotein preparation.

The language “substantially free of chemical precursors or otherchemicals” includes preparations of the variant protein in which it isseparated from chemical precursors or other chemicals that are involvedin its synthesis. In one embodiment, the language “substantially free ofchemical precursors or other chemicals” includes preparations of thevariant protein having less than about 30% (by dry weight) chemicalprecursors or other chemicals, less than about 20% chemical precursorsor other chemicals, less than about 10% chemical precursors or otherchemicals, or less than about 5% chemical precursors or other chemicals.

An isolated variant protein may be purified from cells that naturallyexpress it, purified from cells that have been altered to express it(recombinant host cells), or synthesized using known protein synthesismethods. For example, a nucleic acid molecule containing SNP(s) encodingthe variant protein can be cloned into an expression vector, theexpression vector introduced into a host cell, and the variant proteinexpressed in the host cell. The variant protein can then be isolatedfrom the cells by any appropriate purification scheme using standardprotein purification techniques. Examples of these techniques aredescribed in detail below (Sambrook and Russell, 2000, MolecularCloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, ColdSpring Harbor, N.Y.).

The present invention provides isolated variant proteins that comprise,consist of or consist essentially of amino acid sequences that containone or more variant amino acids encoded by one or more codons whichcontain a SNP of the present invention.

Accordingly, the present invention provides variant proteins thatconsist of amino acid sequences that contain one or more amino acidpolymorphisms (or truncations or extensions due to creation ordestruction of a stop codon, respectively) encoded by the SNPs providedin Table 1 and/or Table 2. A protein consists of an amino acid sequencewhen the amino acid sequence is the entire amino acid sequence of theprotein.

The present invention further provides variant proteins that consistessentially of amino acid sequences that contain one or more amino acidpolymorphisms (or truncations or extensions due to creation ordestruction of a stop codon, respectively) encoded by the SNPs providedin Table 1 and/or Table 2. A protein consists essentially of an aminoacid sequence when such an amino acid sequence is present with only afew additional amino acid residues in the final protein.

The present invention further provides variant proteins that compriseamino acid sequences that contain one or more amino acid polymorphisms(or truncations or extensions due to creation or destruction of a stopcodon, respectively) encoded by the SNPs provided in Table 1 and/orTable 2. A protein comprises an amino acid sequence when the amino acidsequence is at least part of the final amino acid sequence of theprotein. In such a fashion, the protein may contain only the variantamino acid sequence or have additional amino acid residues, such as acontiguous encoded sequence that is naturally associated with it orheterologous amino acid residues. Such a protein can have a fewadditional amino acid residues or can comprise many more additionalamino acids. A brief description of how various types of these proteinscan be made and isolated is provided below.

The variant proteins of the present invention can be attached toheterologous sequences to form chimeric or fusion proteins. Suchchimeric and fusion proteins comprise a variant protein operativelylinked to a heterologous protein having an amino acid sequence notsubstantially homologous to the variant protein. “Operatively linked”indicates that the coding sequences for the variant protein and theheterologous protein are ligated in-frame. The heterologous protein canbe fused to the N-terminus or C-terminus of the variant protein. Inanother embodiment, the fusion protein is encoded by a fusionpolynucleotide that is synthesized by conventional techniques includingautomated DNA synthesizers. Alternatively, PCR amplification of genefragments can be carried out using anchor primers which give rise tocomplementary overhangs between two consecutive gene fragments which cansubsequently be annealed and re-amplified to generate a chimeric genesequence (see Ausubel et al., Current Protocols in Molecular Biology,1992). Moreover, many expression vectors are commercially available thatalready encode a fusion moiety (e.g., a GST protein). A variantprotein-encoding nucleic acid can be cloned into such an expressionvector such that the fusion moiety is linked in-frame to the variantprotein.

In many uses, the fusion protein does not affect the activity of thevariant protein. The fusion protein can include, but is not limited to,enzymatic fusion proteins, for example, beta-galactosidase fusions,yeast two-hybrid GAL fusions, poly-His fusions, MYC-tagged, HI-taggedand Ig fusions. Such fusion proteins, particularly poly-His fusions, canfacilitate their purification following recombinant expression. Incertain host cells (e.g., mammalian host cells), expression and/orsecretion of a protein can be increased by using a heterologous signalsequence. Fusion proteins are further described in, for example, Terpe,“Overview of tag protein fusions: from molecular and biochemicalfundamentals to commercial systems”, Appl Microbiol Biotechnol. 2003January; 60(5):523-33. Epub 2002 Nov. 7; Graddis et al., “Designingproteins that work using recombinant technologies”, Curr PharmBiotechnol. 2002 December; 3(4):285-97; and Nilsson et al., “Affinityfusion strategies for detection, purification, and immobilization ofrecombinant proteins”, Protein Expr Purif. 1997 October; 11(1):1-16.

The present invention also relates to further obvious variants of thevariant polypeptides of the present invention, such asnaturally-occurring mature forms (e.g., alleleic variants),non-naturally occurring recombinantly-derived variants, and orthologsand paralogs of such proteins that share sequence homology. Suchvariants can readily be generated using art-known techniques in thefields of recombinant nucleic acid technology and protein biochemistry.It is understood, however, that variants exclude those known in theprior art before the present invention.

Further variants of the variant polypeptides disclosed in Table 1 cancomprise an amino acid sequence that shares at least 70-80%, 80-85%,85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% sequence identitywith an amino acid sequence disclosed in Table 1 (or a fragment thereof)and that includes a novel amino acid residue (allele) disclosed in Table1 (which is encoded by a novel SNP allele). Thus, an aspect of thepresent invention that is specifically contemplated are polypeptidesthat have a certain degree of sequence variation compared with thepolypeptide sequences shown in Table 1, but that contain a novel aminoacid residue (allele) encoded by a novel SNP allele disclosed herein. Inother words, as long as a polypeptide contains a novel amino acidresidue disclosed herein, other portions of the polypeptide that flankthe novel amino acid residue can vary to some degree from thepolypeptide sequences shown in Table 1.

Full-length pre-processed forms, as well as mature processed forms, ofproteins that comprise one of the amino acid sequences disclosed hereincan readily be identified as having complete sequence identity to one ofthe variant proteins of the present invention as well as being encodedby the same genetic locus as the variant proteins provided herein.

Orthologs of a variant peptide can readily be identified as having somedegree of significant sequence homology/identity to at least a portionof a variant peptide as well as being encoded by a gene from anotherorganism. Preferred orthologs will be isolated from non-human mammals,preferably primates, for the development of human therapeutic targetsand agents. Such orthologs can be encoded by a nucleic acid sequencethat hybridizes to a variant peptide-encoding nucleic acid moleculeunder moderate to stringent conditions depending on the degree ofrelatedness of the two organisms yielding the homologous proteins.

Variant proteins include, but are not limited to, proteins containingdeletions, additions and substitutions in the amino acid sequence causedby the SNPs of the present invention. One class of substitutions isconserved amino acid substitutions in which a given amino acid in apolypeptide is substituted for another amino acid of likecharacteristics. Typical conservative substitutions are replacements,one for another, among the aliphatic amino acids Ala, Val, Leu, and Be;interchange of the hydroxyl residues Ser and Thr; exchange of the acidicresidues Asp and Glu; substitution between the amide residues Asn andGln; exchange of the basic residues Lys and Arg; and replacements amongthe aromatic residues Phe and Tyr. Guidance concerning which amino acidchanges are likely to be phenotypically silent are found in, forexample, Bowie et al., Science 247:1306-1310 (1990).

Variant proteins can be fully functional or can lack function in one ormore activities, e.g. ability to bind another molecule, ability tocatalyze a substrate, ability to mediate signaling, etc. Fullyfunctional variants typically contain only conservative variations orvariations in non-critical residues or in non-critical regions.Functional variants can also contain substitution of similar amino acidsthat result in no change or an insignificant change in function.Alternatively, such substitutions may positively or negatively affectfunction to some degree. Non-functional variants typically contain oneor more non-conservative amino acid substitutions, deletions,insertions, inversions, truncations or extensions, or a substitution,insertion, inversion, or deletion of a critical residue or in a criticalregion.

Amino acids that are essential for function of a protein can beidentified by methods known in the art, such as site-directedmutagenesis or alanine-scanning mutagenesis (Cunningham et al., Science244:1081-1085 (1989)), particularly using the amino acid sequence andpolymorphism information provided in Table 1. The latter procedureintroduces single alanine mutations at every residue in the molecule.The resulting mutant molecules are then tested for biological activitysuch as enzyme activity or in assays such as an in vitro proliferativeactivity. Sites that are critical for binding partner/substrate bindingcan also be determined by structural analysis such as crystallization,nuclear magnetic resonance or photoaffinity labeling (Smith et al., J.Mol. Biol. 224:899-904 (1992); de Vos et al. Science 255:306-312(1992)).

Polypeptides can contain amino acids other than the 20 amino acidscommonly referred to as the 20 naturally occurring amino acids. Further,many amino acids, including the terminal amino acids, may be modified bynatural processes, such as processing and other post-translationalmodifications, or by chemical modification techniques well known in theart. Accordingly, the variant proteins of the present invention alsoencompass derivatives or analogs in which a substituted amino acidresidue is not one encoded by the genetic code, in which a substituentgroup is included, in which the mature polypeptide is fused with anothercompound, such as a compound to increase the half-life of thepolypeptide (e.g., polyethylene glycol), or in which additional aminoacids are fused to the mature polypeptide, such as a leader or secretorysequence or a sequence for purification of the mature polypeptide or apro-protein sequence.

Known protein modifications include, but are not limited to,acetylation, acylation, ADP-ribosylation, amidation, covalent attachmentof flavin, covalent attachment of a heme moiety, covalent attachment ofa nucleotide or nucleotide derivative, covalent attachment of a lipid orlipid derivative, covalent attachment of phosphotidylinositol,cross-linking, cyclization, disulfide bond formation, demethylation,formation of covalent crosslinks, formation of cystine, formation ofpyroglutamate, formylation, gamma carboxylation, glycosylation, GPIanchor formation, hydroxylation, iodination, methylation,myristoylation, oxidation, proteolytic processing, phosphorylation,prenylation, racemization, selenoylation, sulfation, transfer-RNAmediated addition of amino acids to proteins such as arginylation, andubiquitination.

Such protein modifications are well known to those of skill in the artand have been described in great detail in the scientific literature.Several particularly common modifications, glycosylation, lipidattachment, sulfation, gamma-carboxylation of glutamic acid residues,hydroxylation and ADP-ribosylation, for instance, are described in mostbasic texts, such as Proteins—Structure and Molecular Properties, 2ndEd., T. E. Creighton, W. H. Freeman and Company, New York (1993); Wold,F., Posttranslational Covalent Modification of Proteins, B. C. Johnson,Ed., Academic Press, New York 1-12 (1983); Seifter et al., Meth.Enzymol. 182: 626-646 (1990); and Rattan et al., Ann. N.Y. Acad. Sci.663:48-62 (1992).

The present invention further provides fragments of the variant proteinsin which the fragments contain one or more amino acid sequencevariations (e.g., substitutions, or truncations or extensions due tocreation or destruction of a stop codon) encoded by one or more SNPsdisclosed herein. The fragments to which the invention pertains,however, are not to be construed as encompassing fragments that havebeen disclosed in the prior art before the present invention.

As used herein, a fragment may comprise at least about 4, 8, 10, 12, 14,16, 18, 20, 25, 30, 50, 100 (or any other number in-between) or morecontiguous amino acid residues from a variant protein, wherein at leastone amino acid residue is affected by a SNP of the present invention,e.g., a variant amino acid residue encoded by a nonsynonymous nucleotidesubstitution at a cSNP position provided by the present invention. Thevariant amino acid encoded by a cSNP may occupy any residue positionalong the sequence of the fragment. Such fragments can be chosen basedon the ability to retain one or more of the biological activities of thevariant protein or the ability to perform a function, e.g., act as animmunogen. Particularly important fragments are biologically activefragments. Such fragments will typically comprise a domain or motif of avariant protein of the present invention, e.g., active site,transmembrane domain, or ligand/substrate binding domain. Otherfragments include, but are not limited to, domain or motif-containingfragments, soluble peptide fragments, and fragments containingimmunogenic structures. Predicted domains and functional sites arereadily identifiable by computer programs well known to those of skillin the art (e.g., PROSITE analysis) (Current Protocols in ProteinScience, John Wiley & Sons, N.Y. (2002)).

Uses of Variant Proteins

The variant proteins of the present invention can be used in a varietyof ways, including but not limited to, in assays to determine thebiological activity of a variant protein, such as in a panel of multipleproteins for high-throughput screening; to raise antibodies or to elicitanother type of immune response; as a reagent (including the labeledreagent) in assays designed to quantitatively determine levels of thevariant protein (or its binding partner) in biological fluids; as amarker for cells or tissues in which it is preferentially expressed(either constitutively or at a particular stage of tissuedifferentiation or development or in a disease state); as a target forscreening for a therapeutic agent; and as a direct therapeutic agent tobe administered into a human subject. Any of the variant proteinsdisclosed herein may be developed into reagent grade or kit format forcommercialization as research products. Methods for performing the useslisted above are well known to those skilled in the art (see, e.g.,Molecular Cloning: A Laboratory Manual, Cold Spring Harbor LaboratoryPress, Sambrook and Russell, 2000, and Methods in Enzymology: Guide toMolecular Cloning Techniques, Academic Press, Berger, S. L. and A. R.Kimmel eds., 1987).

In a specific embodiment of the invention, the methods of the presentinvention include detection of one or more variant proteins disclosedherein. Variant proteins are disclosed in Table 1 and in the SequenceListing as SEQ ID NOS: 518-1034. Detection of such proteins can beaccomplished using, for example, antibodies, small molecule compounds,aptamers, ligands/substrates, other proteins or protein fragments, orother protein-binding agents. Preferably, protein detection agents arespecific for a variant protein of the present invention and cantherefore discriminate between a variant protein of the presentinvention and the wild-type protein or another variant form. This cangenerally be accomplished by, for example, selecting or designingdetection agents that bind to the region of a protein that differsbetween the variant and wild-type protein, such as a region of a proteinthat contains one or more amino acid substitutions that is/are encodedby a non-synonymous cSNP of the present invention, or a region of aprotein that follows a nonsense mutation-type SNP that creates a stopcodon thereby leading to a shorter polypeptide, or a region of a proteinthat follows a read-through mutation-type SNP that destroys a stop codonthereby leading to a longer polypeptide in which a portion of thepolypeptide is present in one version of the polypeptide but not theother.

In another specific aspect of the invention, the variant proteins of thepresent invention are used as targets for evaluating an individual'spredisposition to developing a cardiovascular disorder, particularly anacute coronary event such as myocardial infarction, or stroke, fortreating and/or preventing cardiovascular disorders, of for predictingan individuals response to statin treatment of cardiovascular disorders,etc. Accordingly, the invention provides methods for detecting thepresence of, or levels of, one or more variant proteins of the presentinvention in a cell, tissue, or organism. Such methods typically involvecontacting a test sample with an agent (e.g., an antibody, smallmolecule compound, or peptide) capable of interacting with the variantprotein such that specific binding of the agent to the variant proteincan be detected. Such an assay can be provided in a single detectionformat or a multi-detection format such as an array, for example, anantibody or aptamer array (arrays for protein detection may also bereferred to as “protein chips”). The variant protein of interest can beisolated from a test sample and assayed for the presence of a variantamino acid sequence encoded by one or more SNPs disclosed by the presentinvention. The SNPs may cause changes to the protein and thecorresponding protein function/activity, such as through non-synonymoussubstitutions in protein coding regions that can lead to amino acidsubstitutions, deletions, insertions, and/or rearrangements; formationor destruction of stop codons; or alteration of control elements such aspromoters. SNPs may also cause inappropriate post-translationalmodifications.

One preferred agent for detecting a variant protein in a sample is anantibody capable of selectively binding to a variant form of the protein(antibodies are described in greater detail in the next section). Suchsamples include, for example, tissues, cells, and biological fluidsisolated from a subject, as well as tissues, cells and fluids presentwithin a subject.

In vitro methods for detection of the variant proteins associated withcardiovascular disorders and/or statin response that are disclosedherein and fragments thereof include, but are not limited to, enzymelinked immunosorbent assays (ELISAs), radioimmunoassays (RIA), Westernblots, immunoprecipitations, immunofluorescence, and proteinarrays/chips (e.g., arrays of antibodies or aptamers). For furtherinformation regarding immunoassays and related protein detectionmethods, see Current Protocols in Immunology, John Wiley & Sons, N.Y.,and Hage, “Immunoassays”, Anal Chem. 1999 Jun. 15; 71(12):294R-304R.

Additional analytic methods of detecting amino acid variants include,but are not limited to, altered electrophoretic mobility, alteredtryptic peptide digest, altered protein activity in cell-based orcell-free assay, alteration in ligand or antibody-binding pattern,altered isoelectric point, and direct amino acid sequencing.

Alternatively, variant proteins can be detected in vivo in a subject byintroducing into the subject a labeled antibody (or other type ofdetection reagent) specific for a variant protein. For example, theantibody can be labeled with a radioactive marker whose presence andlocation in a subject can be detected by standard imaging techniques.

Other uses of the variant peptides of the present invention are based onthe class or action of the protein. For example, proteins isolated fromhumans and their mammalian orthologs serve as targets for identifyingagents (e.g., small molecule drugs or antibodies) for use in therapeuticapplications, particularly for modulating a biological or pathologicalresponse in a cell or tissue that expresses the protein. Pharmaceuticalagents can be developed that modulate protein activity.

As an alternative to modulating gene expression, therapeutic compoundscan be developed that modulate protein function. For example, many SNPsdisclosed herein affect the amino acid sequence of the encoded protein(e.g., non-synonymous cSNPs and nonsense mutation-type SNPs). Suchalterations in the encoded amino acid sequence may affect proteinfunction, particularly if such amino acid sequence variations occur infunctional protein domains, such as catalytic domains, ATP-bindingdomains, or ligand/substrate binding domains. It is well established inthe art that variant proteins having amino acid sequence variations infunctional domains can cause or influence pathological conditions. Insuch instances, compounds (e.g., small molecule drugs or antibodies) canbe developed that target the variant protein and modulate (e.g., up- ordown-regulate) protein function/activity.

The therapeutic methods of the present invention further include methodsthat target one or more variant proteins of the present invention.Variant proteins can be targeted using, for example, small moleculecompounds, antibodies, aptamers, ligands/substrates, other proteins, orother protein-binding agents. Additionally, the skilled artisan willrecognize that the novel protein variants (and polymorphic nucleic acidmolecules) disclosed in Table 1 may themselves be directly used astherapeutic agents by acting as competitive inhibitors of correspondingart-known proteins (or nucleic acid molecules such as mRNA molecules).

The variant proteins of the present invention are particularly useful indrug screening assays, in cell-based or cell-free systems. Cell-basedsystems can utilize cells that naturally express the protein, a biopsyspecimen, or cell cultures. In one embodiment, cell-based assays involverecombinant host cells expressing the variant protein. Cell-free assayscan be used to detect the ability of a compound to directly bind to avariant protein or to the corresponding SNP-containing nucleic acidfragment that encodes the variant protein.

A variant protein of the present invention, as well as appropriatefragments thereof, can be used in high-throughput screening assays totest candidate compounds for the ability to bind and/or modulate theactivity of the variant protein. These candidate compounds can befurther screened against a protein having normal function (e.g., awild-type/non-variant protein) to further determine the effect of thecompound on the protein activity. Furthermore, these compounds can betested in animal or invertebrate systems to determine in vivoactivity/effectiveness. Compounds can be identified that activate(agonists) or inactivate (antagonists) the variant protein, anddifferent compounds can be identified that cause various degrees ofactivation or inactivation of the variant protein.

Further, the variant proteins can be used to screen a compound for theability to stimulate or inhibit interaction between the variant proteinand a target molecule that normally interacts with the protein. Thetarget can be a ligand, a substrate or a binding partner that theprotein normally interacts with (for example, epinephrine ornorepinephrine). Such assays typically include the steps of combiningthe variant protein with a candidate compound under conditions thatallow the variant protein, or fragment thereof, to interact with thetarget molecule, and to detect the formation of a complex between theprotein and the target or to detect the biochemical consequence of theinteraction with the variant protein and the target, such as any of theassociated effects of signal transduction.

Candidate compounds include, for example, 1) peptides such as solublepeptides, including Ig-tailed fusion peptides and members of randompeptide libraries (see, e.g., Lam et al., Nature 354:82-84 (1991);Houghten et al., Nature 354:84-86 (1991)) and combinatorialchemistry-derived molecular libraries made of D- and/or L-configurationamino acids; 2) phosphopeptides (e.g., members of random and partiallydegenerate, directed phosphopeptide libraries, see, e.g., Songyang etal., Cell 72:767-778 (1993)); 3) antibodies (e.g., polyclonal,monoclonal, humanized, anti-idiotypic, chimeric, and single chainantibodies as well as Fab, F(ab′)₂, Fab expression library fragments,and epitope-binding fragments of antibodies); and 4) small organic andinorganic molecules (e.g., molecules obtained from combinatorial andnatural product libraries).

One candidate compound is a soluble fragment of the variant protein thatcompetes for ligand binding. Other candidate compounds include mutantproteins or appropriate fragments containing mutations that affectvariant protein function and thus compete for ligand. Accordingly, afragment that competes for ligand, for example with a higher affinity,or a fragment that binds ligand but does not allow release, isencompassed by the invention.

The invention further includes other end point assays to identifycompounds that modulate (stimulate or inhibit) variant protein activity.The assays typically involve an assay of events in the signaltransduction pathway that indicate protein activity. Thus, theexpression of genes that are up or down-regulated in response to thevariant protein dependent signal cascade can be assayed. In oneembodiment, the regulatory region of such genes can be operably linkedto a marker that is easily detectable, such as luciferase.Alternatively, phosphorylation of the variant protein, or a variantprotein target, could also be measured. Any of the biological orbiochemical functions mediated by the variant protein can be used as anendpoint assay. These include all of the biochemical or biologicalevents described herein, in the references cited herein, incorporated byreference for these endpoint assay targets, and other functions known tothose of ordinary skill in the art.

Binding and/or activating compounds can also be screened by usingchimeric variant proteins in which an amino terminal extracellulardomain or parts thereof, an entire transmembrane domain or subregions,and/or the carboxyl terminal intracellular domain or parts thereof, canbe replaced by heterologous domains or subregions. For example, asubstrate-binding region can be used that interacts with a differentsubstrate than that which is normally recognized by a variant protein.Accordingly, a different set of signal transduction components isavailable as an end-point assay for activation. This allows for assaysto be performed in other than the specific host cell from which thevariant protein is derived.

The variant proteins are also useful in competition binding assays inmethods designed to discover compounds that interact with the variantprotein. Thus, a compound can be exposed to a variant protein underconditions that allow the compound to bind or to otherwise interact withthe variant protein. A binding partner, such as ligand, that normallyinteracts with the variant protein is also added to the mixture. If thetest compound interacts with the variant protein or its binding partner,it decreases the amount of complex formed or activity from the variantprotein. This type of assay is particularly useful in screening forcompounds that interact with specific regions of the variant protein(Hodgson, Bio/technology, 1992, Sep. 10(9), 973-80).

To perform cell-free drug screening assays, it is sometimes desirable toimmobilize either the variant protein or a fragment thereof, or itstarget molecule, to facilitate separation of complexes from uncomplexedforms of one or both of the proteins, as well as to accommodateautomation of the assay. Any method for immobilizing proteins onmatrices can be used in drug screening assays. In one embodiment, afusion protein containing an added domain allows the protein to be boundto a matrix. For example, glutathione-S-transferase/¹²⁵I fusion proteinscan be adsorbed onto glutathione sepharose beads (Sigma Chemical, St.Louis, Mo.) or glutathione derivatized microtitre plates, which are thencombined with the cell lysates (e.g., ³⁵S-labeled) and a candidatecompound, such as a drug candidate, and the mixture incubated underconditions conducive to complex formation (e.g., at physiologicalconditions for salt and pH). Following incubation, the beads can bewashed to remove any unbound label, and the matrix immobilized andradiolabel determined directly, or in the supernatant after thecomplexes are dissociated. Alternatively, the complexes can bedissociated from the matrix, separated by SDS-PAGE, and the level ofbound material found in the bead fraction quantitated from the gel usingstandard electrophoretic techniques.

Either the variant protein or its target molecule can be immobilizedutilizing conjugation of biotin and streptavidin. Alternatively,antibodies reactive with the variant protein but which do not interferewith binding of the variant protein to its target molecule can bederivatized to the wells of the plate, and the variant protein trappedin the wells by antibody conjugation. Preparations of the targetmolecule and a candidate compound are incubated in the variantprotein-presenting wells and the amount of complex trapped in the wellcan be quantitated. Methods for detecting such complexes, in addition tothose described above for the GST-immobilized complexes, includeimmunodetection of complexes using antibodies reactive with the proteintarget molecule, or which are reactive with variant protein and competewith the target molecule, and enzyme-linked assays that rely ondetecting an enzymatic activity associated with the target molecule.

Modulators of variant protein activity identified according to thesedrug screening assays can be used to treat a subject with a disordermediated by the protein pathway, such as cardiovascular disease. Thesemethods of treatment typically include the steps of administering themodulators of protein activity in a pharmaceutical composition to asubject in need of such treatment.

The variant proteins, or fragments thereof, disclosed herein canthemselves be directly used to treat a disorder characterized by anabsence of, inappropriate, or unwanted expression or activity of thevariant protein. Accordingly, methods for treatment include the use of avariant protein disclosed herein or fragments thereof.

In yet another aspect of the invention, variant proteins can be used as“bait proteins” in a two-hybrid assay or three-hybrid assay (see, e.g.,U.S. Pat. No. 5,283,317; Zervos et al. (1993) Cell 72:223-232; Madura etal. (1993) J. Biol. Chem. 268:12046-12054; Bartel et al. (1993)Biotechniques 14:920-924; Iwabuchi et al. (1993) Oncogene 8:1693-1696;and Brent WO94/10300) to identify other proteins that bind to orinteract with the variant protein and are involved in variant proteinactivity. Such variant protein-binding proteins are also likely to beinvolved in the propagation of signals by the variant proteins orvariant protein targets as, for example, elements of a protein-mediatedsignaling pathway. Alternatively, such variant protein-binding proteinsare inhibitors of the variant protein.

The two-hybrid system is based on the modular nature of mosttranscription factors, which typically consist of separable DNA-bindingand activation domains. Briefly, the assay typically utilizes twodifferent DNA constructs. In one construct, the gene that codes for avariant protein is fused to a gene encoding the DNA binding domain of aknown transcription factor (e.g., GAL-4). In the other construct, a DNAsequence, from a library of DNA sequences, that encodes an unidentifiedprotein (“prey” or “sample”) is fused to a gene that codes for theactivation domain of the known transcription factor. If the “bait” andthe “prey” proteins are able to interact, in vivo, forming a variantprotein-dependent complex, the DNA-binding and activation domains of thetranscription factor are brought into close proximity. This proximityallows transcription of a reporter gene (e.g., LacZ) that is operablylinked to a transcriptional regulatory site responsive to thetranscription factor. Expression of the reporter gene can be detected,and cell colonies containing the functional transcription factor can beisolated and used to obtain the cloned gene that encodes the proteinthat interacts with the variant protein.

Antibodies Directed to Variant Proteins

The present invention also provides antibodies that selectively bind tothe variant proteins disclosed herein and fragments thereof. Suchantibodies may be used to quantitatively or qualitatively detect thevariant proteins of the present invention. As used herein, an antibodyselectively binds a target variant protein when it binds the variantprotein and does not significantly bind to non-variant proteins, i.e.,the antibody does not significantly bind to normal, wild-type, orart-known proteins that do not contain a variant amino acid sequence dueto one or more SNPs of the present invention (variant amino acidsequences may be due to, for example, nonsynonymous cSNPs, nonsense SNPsthat create a stop codon, thereby causing a truncation of a polypeptideor SNPs that cause read-through mutations resulting in an extension of apolypeptide).

As used herein, an antibody is defined in terms consistent with thatrecognized in the art: they are multi-subunit proteins produced by anorganism in response to an antigen challenge. The antibodies of thepresent invention include both monoclonal antibodies and polyclonalantibodies, as well as antigen-reactive proteolytic fragments of suchantibodies, such as Fab, F(ab)′₂, and Fv fragments. In addition, anantibody of the present invention further includes any of a variety ofengineered antigen-binding molecules such as a chimeric antibody (U.S.Pat. Nos. 4,816,567 and 4,816,397; Morrison et al., Proc. Natl. Acad.Sci. USA, 81:6851, 1984; Neuberger et al., Nature 312:604, 1984), ahumanized antibody (U.S. Pat. Nos. 5,693,762; 5,585,089; and 5,565,332),a single-chain Fv (U.S. Pat. No. 4,946,778; Ward et al., Nature 334:544,1989), a bispecific antibody with two binding specificities (Segal etal., J. Immunol. Methods 248:1, 2001; Carter, J. Immunol. Methods 248:7,2001), a diabody, a triabody, and a tetrabody (Todorovska et al., J.Immunol. Methods, 248:47, 2001), as well as a Fab conjugate (dimer ortrimer), and a minibody.

Many methods are known in the art for generating and/or identifyingantibodies to a given target antigen (Harlow, Antibodies, Cold SpringHarbor Press, (1989)). In general, an isolated peptide (e.g., a variantprotein of the present invention) is used as an immunogen and isadministered to a mammalian organism, such as a rat, rabbit, hamster ormouse. Either a full-length protein, an antigenic peptide fragment(e.g., a peptide fragment containing a region that varies between avariant protein and a corresponding wild-type protein), or a fusionprotein can be used. A protein used as an immunogen may benaturally-occurring, synthetic or recombinantly produced, and may beadministered in combination with an adjuvant, including but not limitedto, Freund's (complete and incomplete), mineral gels such as aluminumhydroxide, surface active substance such as lysolecithin, pluronicpolyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanin,dinitrophenol, and the like.

Monoclonal antibodies can be produced by hybridoma technology (Kohlerand Milstein, Nature, 256:495, 1975), which immortalizes cells secretinga specific monoclonal antibody. The immortalized cell lines can becreated in vitro by fusing two different cell types, typicallylymphocytes, and tumor cells. The hybridoma cells may be cultivated invitro or in vivo. Additionally, fully human antibodies can be generatedby transgenic animals (He et al., J. Immunol., 169:595, 2002). Fd phageand Fd phagemid technologies may be used to generate and selectrecombinant antibodies in vitro (Hoogenboom and Chames, Immunol. Today21:371, 2000; Liu et al., J. Mol. Biol. 315:1063, 2002). Thecomplementarity-determining regions of an antibody can be identified,and synthetic peptides corresponding to such regions may be used tomediate antigen binding (U.S. Pat. No. 5,637,677).

Antibodies are preferably prepared against regions or discrete fragmentsof a variant protein containing a variant amino acid sequence ascompared to the corresponding wild-type protein (e.g., a region of avariant protein that includes an amino acid encoded by a nonsynonymouscSNP, a region affected by truncation caused by a nonsense SNP thatcreates a stop codon, or a region resulting from the destruction of astop codon due to read-through mutation caused by a SNP). Furthermore,preferred regions will include those involved in function/activityand/or protein/binding partner interaction. Such fragments can beselected on a physical property, such as fragments corresponding toregions that are located on the surface of the protein, e.g.,hydrophilic regions, or can be selected based on sequence uniqueness, orbased on the position of the variant amino acid residue(s) encoded bythe SNPs provided by the present invention. An antigenic fragment willtypically comprise at least about 8-10 contiguous amino acid residues inwhich at least one of the amino acid residues is an amino acid affectedby a SNP disclosed herein. The antigenic peptide can comprise, however,at least 12, 14, 16, 20, 25, 50, 100 (or any other number in-between) ormore amino acid residues, provided that at least one amino acid isaffected by a SNP disclosed herein.

Detection of an antibody of the present invention can be facilitated bycoupling (i.e., physically linking) the antibody or an antigen-reactivefragment thereof to a detectable substance. Detectable substancesinclude, but are not limited to, various enzymes, prosthetic groups,fluorescent materials, luminescent materials, bioluminescent materials,and radioactive materials. Examples of suitable enzymes includehorseradish peroxidase, alkaline phosphatase, β-galactosidase, oracetylcholinesterase; examples of suitable prosthetic group complexesinclude streptavidin/biotin and avidin/biotin; examples of suitablefluorescent materials include umbelliferone, fluorescein, fluoresceinisothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansylchloride or phycoerythrin; an example of a luminescent material includesluminol; examples of bioluminescent materials include luciferase,luciferin, and aequorin, and examples of suitable radioactive materialinclude ¹²⁵I, ¹³¹I, ³⁵S or ³H.

Antibodies, particularly the use of antibodies as therapeutic agents,are reviewed in: Morgan, “Antibody therapy for Alzheimer's disease”,Expert Rev Vaccines. 2003 February; 2(1):53-9; Ross et al., “Anticancerantibodies”, Am J Clin Pathol. 2003 April; 119(4):472-85; Goldenberg,“Advancing role of radiolabeled antibodies in the therapy of cancer”,Cancer Immunol Immunother. 2003 May; 52(5):281-96. Epub 2003 Mar. 11;Ross et al., “Antibody-based therapeutics in oncology”, Expert RevAnticancer Ther. 2003 February; 3(1):107-21; Cao et al., “Bispecificantibody conjugates in therapeutics”, Adv Drug Deliv Rev. 2003 Feb. 10;55(2):171-97; von Mehren et al., “Monoclonal antibody therapy forcancer”, Annu Rev Med. 2003; 54:343-69. Epub 2001 Dec. 3; Hudson et al.,“Engineered antibodies”, Nat Med. 2003 January; 9(1):129-34; Brekke etal., “Therapeutic antibodies for human diseases at the dawn of thetwenty-first century”, Nat Rev Drug Discov. 2003 January; 2(1):52-62(Erratum in: Nat Rev Drug Discov. 2003 March; 2(3):240); Houdebine,“Antibody manufacture in transgenic animals and comparisons with othersystems”, Curr Opin Biotechnol. 2002 December; 13(6):625-9; Andreakos etal., “Monoclonal antibodies in immune and inflammatory diseases”, CurrOpin Biotechnol. 2002 December; 13(6):615-20; Kellermann et al.,“Antibody discovery: the use of transgenic mice to generate humanmonoclonal antibodies for therapeutics”, Curr Opin Biotechnol. 2002December; 13(6):593-7; Pini et al., “Phage display and colony filterscreening for high-throughput selection of antibody libraries”, CombChem High Throughput Screen. 2002 November; 5(7):503-10; Batra et al.,“Pharmacokinetics and biodistribution of genetically engineeredantibodies”, Curr Opin Biotechnol. 2002 December; 13(6):603-8; andTangri et al., “Rationally engineered proteins or antibodies with absentor reduced immunogenicity”, Curr Med Chem. 2002 December; 9(24):2191-9.

Uses of Antibodies

Antibodies can be used to isolate the variant proteins of the presentinvention from a natural cell source or from recombinant host cells bystandard techniques, such as affinity chromatography orimmunoprecipitation. In addition, antibodies are useful for detectingthe presence of a variant protein of the present invention in cells ortissues to determine the pattern of expression of the variant proteinamong various tissues in an organism and over the course of normaldevelopment or disease progression. Further, antibodies can be used todetect variant protein in situ, in vitro, in a bodily fluid, or in acell lysate or supernatant in order to evaluate the amount and patternof expression. Also, antibodies can be used to assess abnormal tissuedistribution, abnormal expression during development, or expression inan abnormal condition, such as in a cardiovascular disorder or duringstatin treatment. Additionally, antibody detection of circulatingfragments of the full-length variant protein can be used to identifyturnover.

Antibodies to the variant proteins of the present invention are alsouseful in pharmacogenomic analysis. Thus, antibodies against variantproteins encoded by alternative SNP alleles can be used to identifyindividuals that require modified treatment modalities.

Further, antibodies can be used to assess expression of the variantprotein in disease states such as in active stages of the disease or inan individual with a predisposition to a disease related to theprotein's function, such as a cardiovascular disorder, or during thecourse of a treatment regime, such as during statin treatment.Antibodies specific for a variant protein encoded by a SNP-containingnucleic acid molecule of the present invention can be used to assay forthe presence of the variant protein, such as to predict an individual'sresponse to statin treatment or predisposition/susceptibility to anacute coronary event, as indicated by the presence of the variantprotein.

Antibodies are also useful as diagnostic tools for evaluating thevariant proteins in conjunction with analysis by electrophoreticmobility, isoelectric point, tryptic peptide digest, and other physicalassays well known in the art.

Antibodies are also useful for tissue typing. Thus, where a specificvariant protein has been correlated with expression in a specifictissue, antibodies that are specific for this protein can be used toidentify a tissue type.

Antibodies can also be used to assess aberrant subcellular localizationof a variant protein in cells in various tissues. The diagnostic usescan be applied, not only in genetic testing, but also in monitoring atreatment modality. Accordingly, where treatment is ultimately aimed atcorrecting the expression level or the presence of variant protein oraberrant tissue distribution or developmental expression of a variantprotein, antibodies directed against the variant protein or relevantfragments can be used to monitor therapeutic efficacy.

The antibodies are also useful for inhibiting variant protein function,for example, by blocking the binding of a variant protein to a bindingpartner. These uses can also be applied in a therapeutic context inwhich treatment involves inhibiting a variant protein's function. Anantibody can be used, for example, to block or competitively inhibitbinding, thus modulating (agonizing or antagonizing) the activity of avariant protein. Antibodies can be prepared against specific variantprotein fragments containing sites required for function or against anintact variant protein that is associated with a cell or cell membrane.For in vivo administration, an antibody may be linked with an additionaltherapeutic payload such as a radionuclide, an enzyme, an immunogenicepitope, or a cytotoxic agent. Suitable cytotoxic agents include, butare not limited to, bacterial toxin such as diphtheria, and plant toxinsuch as ricin. The in vivo half-life of an antibody or a fragmentthereof may be lengthened by pegylation through conjugation topolyethylene glycol (Leong et al., Cytokine 16:106, 2001).

The invention also encompasses kits for using antibodies, such as kitsfor detecting the presence of a variant protein in a test sample. Anexemplary kit can comprise antibodies such as a labeled or labelableantibody and a compound or agent for detecting variant proteins in abiological sample; means for determining the amount, or presence/absenceof variant protein in the sample; means for comparing the amount ofvariant protein in the sample with a standard; and instructions for use.

Vectors and Host Cells

The present invention also provides vectors containing theSNP-containing nucleic acid molecules described herein. The term“vector” refers to a vehicle, preferably a nucleic acid molecule, whichcan transport a SNP-containing nucleic acid molecule. When the vector isa nucleic acid molecule, the SNP-containing nucleic acid molecule can becovalently linked to the vector nucleic acid. Such vectors include, butare not limited to, a plasmid, single or double stranded phage, a singleor double stranded RNA or DNA viral vector, or artificial chromosome,such as a BAC, PAC, YAC, or MAC.

A vector can be maintained in a host cell as an extrachromosomal elementwhere it replicates and produces additional copies of the SNP-containingnucleic acid molecules. Alternatively, the vector may integrate into thehost cell genome and produce additional copies of the SNP-containingnucleic acid molecules when the host cell replicates.

The invention provides vectors for the maintenance (cloning vectors) orvectors for expression (expression vectors) of the SNP-containingnucleic acid molecules. The vectors can function in prokaryotic oreukaryotic cells or in both (shuttle vectors).

Expression vectors typically contain cis-acting regulatory regions thatare operably linked in the vector to the SNP-containing nucleic acidmolecules such that transcription of the SNP-containing nucleic acidmolecules is allowed in a host cell. The SNP-containing nucleic acidmolecules can also be introduced into the host cell with a separatenucleic acid molecule capable of affecting transcription. Thus, thesecond nucleic acid molecule may provide a trans-acting factorinteracting with the cis-regulatory control region to allowtranscription of the SNP-containing nucleic acid molecules from thevector. Alternatively, a trans-acting factor may be supplied by the hostcell. Finally, a trans-acting factor can be produced from the vectoritself. It is understood, however, that in some embodiments,transcription and/or translation of the nucleic acid molecules can occurin a cell-free system.

The regulatory sequences to which the SNP-containing nucleic acidmolecules described herein can be operably linked include promoters fordirecting mRNA transcription. These include, but are not limited to, theleft promoter from bacteriophage λ, the lac, TRP, and TAC promoters fromE. coli, the early and late promoters from SV40, the CMV immediate earlypromoter, the adenovirus early and late promoters, and retroviruslong-terminal repeats.

In addition to control regions that promote transcription, expressionvectors may also include regions that modulate transcription, such asrepressor binding sites and enhancers. Examples include the SV40enhancer, the cytomegalovirus immediate early enhancer, polyomaenhancer, adenovirus enhancers, and retrovirus LTR enhancers.

In addition to containing sites for transcription initiation andcontrol, expression vectors can also contain sequences necessary fortranscription termination and, in the transcribed region, aribosome-binding site for translation. Other regulatory control elementsfor expression include initiation and termination codons as well aspolyadenylation signals. A person of ordinary skill in the art would beaware of the numerous regulatory sequences that are useful in expressionvectors (see, e.g., Sambrook and Russell, 2000, Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Laboratory Press, Cold SpringHarbor, N.Y.).

A variety of expression vectors can be used to express a SNP-containingnucleic acid molecule. Such vectors include chromosomal, episomal, andvirus-derived vectors, for example, vectors derived from bacterialplasmids, from bacteriophage, from yeast episomes, from yeastchromosomal elements, including yeast artificial chromosomes, fromviruses such as baculoviruses, papovaviruses such as SV40, Vacciniaviruses, adenoviruses, poxviruses, pseudorabies viruses, andretroviruses. Vectors can also be derived from combinations of thesesources such as those derived from plasmid and bacteriophage geneticelements, e.g., cosmids and phagemids. Appropriate cloning andexpression vectors for prokaryotic and eukaryotic hosts are described inSambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, ColdSpring Harbor Laboratory Press, Cold Spring Harbor, N.Y.

The regulatory sequence in a vector may provide constitutive expressionin one or more host cells (e.g., tissue specific expression) or mayprovide for inducible expression in one or more cell types such as bytemperature, nutrient additive, or exogenous factor, e.g., a hormone orother ligand. A variety of vectors that provide constitutive orinducible expression of a nucleic acid sequence in prokaryotic andeukaryotic host cells are well known to those of ordinary skill in theart.

A SNP-containing nucleic acid molecule can be inserted into the vectorby methodology well-known in the art. Generally, the SNP-containingnucleic acid molecule that will ultimately be expressed is joined to anexpression vector by cleaving the SNP-containing nucleic acid moleculeand the expression vector with one or more restriction enzymes and thenligating the fragments together. Procedures for restriction enzymedigestion and ligation are well known to those of ordinary skill in theart.

The vector containing the appropriate nucleic acid molecule can beintroduced into an appropriate host cell for propagation or expressionusing well-known techniques. Bacterial host cells include, but are notlimited to, E. coli, Streptomyces, and Salmonella typhimurium.Eukaryotic host cells include, but are not limited to, yeast, insectcells such as Drosophila, animal cells such as COS and CHO cells, andplant cells.

As described herein, it may be desirable to express the variant peptideas a fusion protein. Accordingly, the invention provides fusion vectorsthat allow for the production of the variant peptides. Fusion vectorscan, for example, increase the expression of a recombinant protein,increase the solubility of the recombinant protein, and aid in thepurification of the protein by acting, for example, as a ligand foraffinity purification. A proteolytic cleavage site may be introduced atthe junction of the fusion moiety so that the desired variant peptidecan ultimately be separated from the fusion moiety. Proteolytic enzymessuitable for such use include, but are not limited to, factor Xa,thrombin, and enterokinase. Typical fusion expression vectors includepGEX (Smith et al., Gene 67:31-40 (1988)), pMAL (New England Biolabs,Beverly, Mass.) and pRIT5 (Pharmacia, Piscataway, N.J.) which fuseglutathione S-transferase (GST), maltose E binding protein, or proteinA, respectively, to the target recombinant protein. Examples of suitableinducible non-fusion E. coli expression vectors include pTrc (Amann etal., Gene 69:301-315 (1988)) and pET 11d (Studier et al., GeneExpression Technology: Methods in Enzymology 185:60-89 (1990)).

Recombinant protein expression can be maximized in a bacterial host byproviding a genetic background wherein the host cell has an impairedcapacity to proteolytically cleave the recombinant protein (Gottesman,S., Gene Expression Technology: Methods in Enzymology 185, AcademicPress, San Diego, Calif. (1990) 119-128). Alternatively, the sequence ofthe SNP-containing nucleic acid molecule of interest can be altered toprovide preferential codon usage for a specific host cell, for example,E. coli (Wada et al., Nucleic Acids Res. 20:2111-2118 (1992)).

The SNP-containing nucleic acid molecules can also be expressed byexpression vectors that are operative in yeast. Examples of vectors forexpression in yeast (e.g., S. cerevisiae) include pYepSec1 (Baldari, etal., EMBO J. 6:229-234 (1987)), pMFa (Kurjan et al., Cell30:933-943(1982)), pJRY88 (Schultz et al., Gene 54:113-123 (1987)), andpYES2 (Invitrogen Corporation, San Diego, Calif.).

The SNP-containing nucleic acid molecules can also be expressed ininsect cells using, for example, baculovirus expression vectors.Baculovirus vectors available for expression of proteins in culturedinsect cells (e.g., Sf 9 cells) include the pAc series (Smith et al.,Mol. Cell Biol. 3:2156-2165 (1983)) and the pVL series (Lucklow et al.,Virology 170:31-39 (1989)).

In certain embodiments of the invention, the SNP-containing nucleic acidmolecules described herein are expressed in mammalian cells usingmammalian expression vectors. Examples of mammalian expression vectorsinclude pCDM8 (Seed, B. Nature 329:840(1987)) and pMT2PC (Kaufman etal., EMBO J. 6:187-195 (1987)).

The invention also encompasses vectors in which the SNP-containingnucleic acid molecules described herein are cloned into the vector inreverse orientation, but operably linked to a regulatory sequence thatpermits transcription of antisense RNA. Thus, an antisense transcriptcan be produced to the SNP-containing nucleic acid sequences describedherein, including both coding and non-coding regions. Expression of thisantisense RNA is subject to each of the parameters described above inrelation to expression of the sense RNA (regulatory sequences,constitutive or inducible expression, tissue-specific expression).

The invention also relates to recombinant host cells containing thevectors described herein. Host cells therefore include, for example,prokaryotic cells, lower eukaryotic cells such as yeast, othereukaryotic cells such as insect cells, and higher eukaryotic cells suchas mammalian cells.

The recombinant host cells can be prepared by introducing the vectorconstructs described herein into the cells by techniques readilyavailable to persons of ordinary skill in the art. These include, butare not limited to, calcium phosphate transfection,DEAE-dextran-mediated transfection, cationic lipid-mediatedtransfection, electroporation, transduction, infection, lipofection, andother techniques such as those described in Sambrook and Russell, 2000,Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory,Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.).

Host cells can contain more than one vector. Thus, differentSNP-containing nucleotide sequences can be introduced in differentvectors into the same cell. Similarly, the SNP-containing nucleic acidmolecules can be introduced either alone or with other nucleic acidmolecules that are not related to the SNP-containing nucleic acidmolecules, such as those providing trans-acting factors for expressionvectors. When more than one vector is introduced into a cell, thevectors can be introduced independently, co-introduced, or joined to thenucleic acid molecule vector.

In the case of bacteriophage and viral vectors, these can be introducedinto cells as packaged or encapsulated virus by standard procedures forinfection and transduction. Viral vectors can be replication-competentor replication-defective. In the case in which viral replication isdefective, replication can occur in host cells that provide functionsthat complement the defects.

Vectors generally include selectable markers that enable the selectionof the subpopulation of cells that contain the recombinant vectorconstructs. The marker can be inserted in the same vector that containsthe SNP-containing nucleic acid molecules described herein or may be ina separate vector. Markers include, for example, tetracycline orampicillin-resistance genes for prokaryotic host cells, anddihydrofolate reductase or neomycin resistance genes for eukaryotic hostcells. However, any marker that provides selection for a phenotypictrait can be effective.

While the mature variant proteins can be produced in bacteria, yeast,mammalian cells, and other cells under the control of the appropriateregulatory sequences, cell-free transcription and translation systemscan also be used to produce these variant proteins using RNA derivedfrom the DNA constructs described herein.

Where secretion of the variant protein is desired, which is difficult toachieve with multi-transmembrane domain containing proteins such asG-protein-coupled receptors (GPCRs), appropriate secretion signals canbe incorporated into the vector. The signal sequence can be endogenousto the peptides or heterologous to these peptides.

Where the variant protein is not secreted into the medium, the proteincan be isolated from the host cell by standard disruption procedures,including freeze/thaw, sonication, mechanical disruption, use of lysingagents, and the like. The variant protein can then be recovered andpurified by well-known purification methods including, for example,ammonium sulfate precipitation, acid extraction, anion or cationicexchange chromatography, phosphocellulose chromatography,hydrophobic-interaction chromatography, affinity chromatography,hydroxylapatite chromatography, lectin chromatography, or highperformance liquid chromatography.

It is also understood that, depending upon the host cell in whichrecombinant production of the variant proteins described herein occurs,they can have various glycosylation patterns, or may benon-glycosylated, as when produced in bacteria. In addition, the variantproteins may include an initial modified methionine in some cases as aresult of a host-mediated process.

For further information regarding vectors and host cells, see CurrentProtocols in Molecular Biology, John Wiley & Sons, N.Y.

Uses of Vectors and Host Cells, and Transgenic Animals

Recombinant host cells that express the variant proteins describedherein have a variety of uses. For example, the cells are useful forproducing a variant protein that can be further purified into apreparation of desired amounts of the variant protein or fragmentsthereof. Thus, host cells containing expression vectors are useful forvariant protein production.

Host cells are also useful for conducting cell-based assays involvingthe variant protein or variant protein fragments, such as thosedescribed above as well as other formats known in the art. Thus, arecombinant host cell expressing a variant protein is useful forassaying compounds that stimulate or inhibit variant protein function.Such an ability of a compound to modulate variant protein function maynot be apparent from assays of the compound on the native/wild-typeprotein, or from cell-free assays of the compound. Recombinant hostcells are also useful for assaying functional alterations in the variantproteins as compared with a known function.

Genetically-engineered host cells can be further used to producenon-human transgenic animals. A transgenic animal is preferably anon-human mammal, for example, a rodent, such as a rat or mouse, inwhich one or more of the cells of the animal include a transgene. Atransgene is exogenous DNA containing a SNP of the present inventionwhich is integrated into the genome of a cell from which a transgenicanimal develops and which remains in the genome of the mature animal inone or more of its cell types or tissues. Such animals are useful forstudying the function of a variant protein in vivo, and identifying andevaluating modulators of variant protein activity. Other examples oftransgenic animals include, but are not limited to, non-human primates,sheep, dogs, cows, goats, chickens, and amphibians. Transgenic non-humanmammals such as cows and goats can be used to produce variant proteinswhich can be secreted in the animal's milk and then recovered.

A transgenic animal can be produced by introducing a SNP-containingnucleic acid molecule into the male pronuclei of a fertilized oocyte,e.g., by microinjection or retroviral infection, and allowing the oocyteto develop in a pseudopregnant female foster animal. Any nucleic acidmolecules that contain one or more SNPs of the present invention canpotentially be introduced as a transgene into the genome of a non-humananimal.

Any of the regulatory or other sequences useful in expression vectorscan form part of the transgenic sequence. This includes intronicsequences and polyadenylation signals, if not already included. Atissue-specific regulatory sequence(s) can be operably linked to thetransgene to direct expression of the variant protein in particularcells or tissues.

Methods for generating transgenic animals via embryo manipulation andmicroinjection, particularly animals such as mice, have becomeconventional in the art and are described in, for example, U.S. Pat.Nos. 4,736,866 and 4,870,009, both by Leder et al., U.S. Pat. No.4,873,191 by Wagner et al., and in Hogan, B., Manipulating the MouseEmbryo, (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.,1986). Similar methods are used for production of other transgenicanimals. A transgenic founder animal can be identified based upon thepresence of the transgene in its genome and/or expression of transgenicmRNA in tissues or cells of the animals. A transgenic founder animal canthen be used to breed additional animals carrying the transgene.Moreover, transgenic animals carrying a transgene can further be bred toother transgenic animals carrying other transgenes. A transgenic animalalso includes a non-human animal in which the entire animal or tissuesin the animal have been produced using the homologously recombinant hostcells described herein.

In another embodiment, transgenic non-human animals can be producedwhich contain selected systems that allow for regulated expression ofthe transgene. One example of such a system is the cre/loxP recombinasesystem of bacteriophage P1 (Lakso et al. PNAS 89:6232-6236 (1992)).Another example of a recombinase system is the FLP recombinase system ofS. cerevisiae (O'Gorman et al. Science 251:1351-1355 (1991)). If acre/loxP recombinase system is used to regulate expression of thetransgene, animals containing transgenes encoding both the Crerecombinase and a selected protein are generally needed. Such animalscan be provided through the construction of “double” transgenic animals,e.g., by mating two transgenic animals, one containing a transgeneencoding a selected variant protein and the other containing a transgeneencoding a recombinase.

Clones of the non-human transgenic animals described herein can also beproduced according to the methods described in, for example, Wilmut, I.et al. Nature 385:810-813 (1997) and PCT International Publication Nos.WO 97/07668 and WO 97/07669. In brief, a cell (e.g., a somatic cell)from the transgenic animal can be isolated and induced to exit thegrowth cycle and enter G_(o) phase. The quiescent cell can then befused, e.g., through the use of electrical pulses, to an enucleatedoocyte from an animal of the same species from which the quiescent cellis isolated. The reconstructed oocyte is then cultured such that itdevelops to morula or blastocyst and then transferred to pseudopregnantfemale foster animal. The offspring born of this female foster animalwill be a clone of the animal from which the cell (e.g., a somatic cell)is isolated.

Transgenic animals containing recombinant cells that express the variantproteins described herein are useful for conducting the assays describedherein in an in vivo context. Accordingly, the various physiologicalfactors that are present in vivo and that could influence ligand orsubstrate binding, variant protein activation, signal transduction, orother processes or interactions, may not be evident from in vitrocell-free or cell-based assays. Thus, non-human transgenic animals ofthe present invention may be used to assay in vivo variant proteinfunction as well as the activities of a therapeutic agent or compoundthat modulates variant protein function/activity or expression. Suchanimals are also suitable for assessing the effects of null mutations(i.e., mutations that substantially or completely eliminate one or morevariant protein functions).

For further information regarding transgenic animals, see Houdebine,“Antibody manufacture in transgenic animals and comparisons with othersystems”, Curr Opin Biotechnol. 2002 December; 13(6):625-9; Petters etal., “Transgenic animals as models for human disease”, Transgenic Res.2000; 9(4-5):347-51; discussion 345-6; Wolf et al., “Use of transgenicanimals in understanding molecular mechanisms of toxicity”, J PharmPharmacol. 1998 June; 50(6):567-74; Echelard, “Recombinant proteinproduction in transgenic animals”, Curr Opin Biotechnol. 1996 October;7(5):536-40; Houdebine, “Transgenic animal bioreactors”, Transgenic Res.2000; 9(4-5):305-20; Pirity et al., “Embryonic stem cells, creatingtransgenic animals”, Methods Cell Biol. 1998; 57:279-93; and Robl etal., “Artificial chromosome vectors and expression of complex proteinsin transgenic animals”, Theriogenology. 2003 Jan. 1; 59(1):107-13.

Computer-Related Embodiments

The SNPs provided in the present invention may be “provided” in avariety of mediums to facilitate use thereof. As used in this section,“provided” refers to a manufacture, other than an isolated nucleic acidmolecule, that contains SNP information of the present invention. Such amanufacture provides the SNP information in a form that allows a skilledartisan to examine the manufacture using means not directly applicableto examining the SNPs or a subset thereof as they exist in nature or inpurified form. The SNP information that may be provided in such a formincludes any of the SNP information provided by the present inventionsuch as, for example, polymorphic nucleic acid and/or amino acidsequence information such as SEQ ID NOS:1-517, SEQ ID NOS:518-1034, SEQID NOS:13,194-13,514, SEQ ID NOS:1035-13,193, and SEQ IDNOS:13,515-85,090; information about observed SNP alleles, alternativecodons, populations, allele frequencies, SNP types, and/or affectedproteins; or any other information provided by the present invention inTables 1-2 and/or the Sequence Listing.

In one application of this embodiment, the SNPs of the present inventioncan be recorded on a computer readable medium. As used herein, “computerreadable medium” refers to any medium that can be read and accesseddirectly by a computer. Such media include, but are not limited to:magnetic storage media, such as floppy discs, hard disc storage medium,and magnetic tape; optical storage media such as CD-ROM; electricalstorage media such as RAM and ROM; and hybrids of these categories suchas magnetic/optical storage media. A skilled artisan can readilyappreciate how any of the presently known computer readable media can beused to create a manufacture comprising computer readable medium havingrecorded thereon a nucleotide sequence of the present invention. Onesuch medium is provided with the present application, namely, thepresent application contains computer readable medium (CD-R) that hasnucleic acid sequences (and encoded protein sequences) containing SNPsprovided/recorded thereon in ASCII text format in a Sequence Listingalong with accompanying Tables that contain detailed SNP and sequenceinformation (transcript sequences are provided as SEQ ID NOS:1-517,protein sequences are provided as SEQ ID NOS:518-1034, genomic sequencesare provided as SEQ ID NOS:13,194-13,514, transcript-based contextsequences are provided as SEQ ID NOS:1035-13,193, and genomic-basedcontext sequences are provided as SEQ ID NOS:13,515-85,090).

As used herein, “recorded” refers to a process for storing informationon computer readable medium. A skilled artisan can readily adopt any ofthe presently known methods for recording information on computerreadable medium to generate manufactures comprising the SNP informationof the present invention.

A variety of data storage structures are available to a skilled artisanfor creating a computer readable medium having recorded thereon anucleotide or amino acid sequence of the present invention. The choiceof the data storage structure will generally be based on the meanschosen to access the stored information. In addition, a variety of dataprocessor programs and formats can be used to store the nucleotide/aminoacid sequence information of the present invention on computer readablemedium. For example, the sequence information can be represented in aword processing text file, formatted in commercially-available softwaresuch as WordPerfect and Microsoft Word, represented in the form of anASCII file, or stored in a database application, such as OB2, Sybase,Oracle, or the like. A skilled artisan can readily adapt any number ofdata processor structuring formats (e.g., text file or database) inorder to obtain computer readable medium having recorded thereon the SNPinformation of the present invention.

By providing the SNPs of the present invention in computer readableform, a skilled artisan can routinely access the SNP information for avariety of purposes. Computer software is publicly available whichallows a skilled artisan to access sequence information provided in acomputer readable medium. Examples of publicly available computersoftware include BLAST (Altschul et at, J. Mol. Biol. 215:403-410(1990)) and BLAZE (Brutlag et at, Comp. Chem. 17:203-207 (1993)) searchalgorithms.

The present invention further provides systems, particularlycomputer-based systems, which contain the SNP information describedherein. Such systems may be designed to store and/or analyze informationon, for example, a large number of SNP positions, or information on SNPgenotypes from a large number of individuals. The SNP information of thepresent invention represents a valuable information source. The SNPinformation of the present invention stored/analyzed in a computer-basedsystem may be used for such computer-intensive applications asdetermining or analyzing SNP allele frequencies in a population, mappingdisease genes, genotype-phenotype association studies, grouping SNPsinto haplotypes, correlating SNP haplotypes with response to particulardrugs, or for various other bioinformatic, pharmacogenomic, drugdevelopment, or human identification/forensic applications.

As used herein, “a computer-based system” refers to the hardware means,software means, and data storage means used to analyze the SNPinformation of the present invention. The minimum hardware means of thecomputer-based systems of the present invention typically comprises acentral processing unit (CPU), input means, output means, and datastorage means. A skilled artisan can readily appreciate that any one ofthe currently available computer-based systems are suitable for use inthe present invention. Such a system can be changed into a system of thepresent invention by utilizing the SNP information provided on the CD-R,or a subset thereof, without any experimentation.

As stated above, the computer-based systems of the present inventioncomprise a data storage means having stored therein SNPs of the presentinvention and the necessary hardware means and software means forsupporting and implementing a search means. As used herein, “datastorage means” refers to memory which can store SNP information of thepresent invention, or a memory access means which can accessmanufactures having recorded thereon the SNP information of the presentinvention.

As used herein, “search means” refers to one or more programs oralgorithms that are implemented on the computer-based system to identifyor analyze SNPs in a target sequence based on the SNP information storedwithin the data storage means. Search means can be used to determinewhich nucleotide is present at a particular SNP position in the targetsequence. As used herein, a “target sequence” can be any DNA sequencecontaining the SNP position(s) to be searched or queried.

As used herein, “a target structural motif,” or “target motif,” refersto any rationally selected sequence or combination of sequencescontaining a SNP position in which the sequence(s) is chosen based on athree-dimensional configuration that is formed upon the folding of thetarget motif. There are a variety of target motifs known in the art.Protein target motifs include, but are not limited to, enzymatic activesites and signal sequences. Nucleic acid target motifs include, but arenot limited to, promoter sequences, hairpin structures, and inducibleexpression elements (protein binding sequences).

A variety of structural formats for the input and output means can beused to input and output the information in the computer-based systemsof the present invention. An exemplary format for an output means is adisplay that depicts the presence or absence of specified nucleotides(alleles) at particular SNP positions of interest. Such presentation canprovide a rapid, binary scoring system for many SNPs simultaneously.

One exemplary embodiment of a computer-based system comprising SNPinformation of the present invention is provided in FIG. 1. FIG. 1provides a block diagram of a computer system 102 that can be used toimplement the present invention. The computer system 102 includes aprocessor 106 connected to a bus 104. Also connected to the bus 104 area main memory 108 (preferably implemented as random access memory, RAM)and a variety of secondary storage devices 110, such as a hard drive 112and a removable medium storage device 114. The removable medium storagedevice 114 may represent, for example, a floppy disk drive, a CD-ROMdrive, a magnetic tape drive, etc. A removable storage medium 116 (suchas a floppy disk, a compact disk, a magnetic tape, etc.) containingcontrol logic and/or data recorded therein may be inserted into theremovable medium storage device 114. The computer system 102 includesappropriate software for reading the control logic and/or the data fromthe removable storage medium 116 once inserted in the removable mediumstorage device 114.

The SNP information of the present invention may be stored in awell-known manner in the main memory 108, any of the secondary storagedevices 110, and/or a removable storage medium 116. Software foraccessing and processing the SNP information (such as SNP scoring tools,search tools, comparing tools, etc.) preferably resides in main memory108 during execution.

EXAMPLES

The following examples are offered to illustrate, but not to limit theclaimed invention.

Example 1: Statistical Analysis of SNP Allele Association withCardiovascular Disorders and Statin Response

Study Design

In order to identify genetic markers associated with acute coronaryevents (e.g. MI, stroke, unstable angina, congestive heart failure,etc.) or response to statin treatment for the prevention of coronaryevents, samples from the Cholesterol and Recurrent Events (CARE) study(a randomized multicentral double-blinded trial on secondary preventionof acute coronary events with pravastatin) (Sacks et al., 1991, Am. J.Cardiol. 68: 1436-1446) were genotyped. A well-documented myocardialinfarction (MI) was one of the enrollment criteria for for entry intothe CARE study. Patients were enrolled in the CARE trial from 80participating study centers. Men and post-menopausal women were eligiblefor the trial if they had had an acute MI between 3 and 20 months priorto randomization, were 21 to 75 years of age, and had plasma totalcholesterol levels of less than 240 mg/deciliter, LDL cholesterol levelsof 115 to 174 mgs/deciliter, fasting triglyceride levels of less than350 mgs/deciliter, fasting glucose levels of no more than 220mgs/deciliter, left ventricular ejection fractions of no less than 25%,and no symptomatic congestive heart failure. Patients were randomized toreceive either 40 mg of pravastatin once daily or a matching placebo.The primary endpoint of the trial was death from coronary heart diseaseand the median duration of follow-up was 5.0 years (range, 4.0 to 6.2years). Patients enrolled in the CARE study who received placebo had a 5year risk of having a recurrent MI (RMI) of 9.5% while those patientsenrolled in the study that received pravastatin had a 5 year risk ofhaving a RMI of only 7.2% (p_(LogRank)=0.0234) (25% reduction in riskfor RMI in treatment vs. placebo groups, Cox Proportional Hazard Ratio[HR_(age-adjusted)]=0.75 [95% CI: 0.58-0.97, p=0.0256]). Secondaryendpoints of other related cardiovascular or metabolic disease events,and changes in clinical variables were also recorded inpravastatin-treated and placebo groups. Examples of secondary endpointsare listed in Tables 6-8. All individuals included in the study hadsigned a written informed consent form and the study protocol wasapproved by the respective Institutional Review Boards (IRBs).

For genotyping SNPs in CARE patient samples, DNA was extracted fromblood samples using conventional DNA extraction methods such as theQIA-amp kit from Qiagen. Allele specific primers were designed fordetecting each SNP and they are shown in Table 5. Genotypes wereobtained on an ABI PRISM® 7900HT Sequence Detection PCR system (AppliedBiosystems, Foster City, Calif.) by kinetic allele-specific PCR, similarto the method described by Germer et al. (Germer S., Holland M. J.,Higuchi R. 2000, Genome Res. 10: 258-266).

In the first analysis of samples obtained from patients enrolled in theCARE study, SNP genotype frequencies in a group of 264 patients who hada second MI during the 5 years of CARE follow-up (cases) were comparedwith the frequencies in the group of 1255 CARE patients who had notexperienced second MI (controls). Logistic regression was used to adjustfor the major epidemiologic risk factors with the specific emphasis onthe interaction between the risk factors and tested SNPs to identifySNPs significantly associated with RMI when patients were stratified bysex, family history, smoking status, body mass index (BMI), ApoE statusor hypertension.

To replicate initial findings, a second group of 394 CARE patients wereanalyzed who had a history of an MI prior to the MI at CARE enrollment(i.e., patients who had experienced a RMI at enrollment) but who had notexperienced an MI during trial follow-up (cases), and 1221 of CARE MIpatients without second MI were used as controls. No patients from firstanalysis (cases or controls) were used in this second analysis (cases orcontrols). There are significant clinical differences between the twoanalyses e.g., in the first analysis, all MI patients were in acarefully monitored clinical environment prior to their second MI, whichcould modulate effect of genetic polymorphisms, whereas in the secondanalysis, only a small portion of patients were treated by lipidlowering drugs prior to second MI. Despite these differences, numerousmarkers associated with RMI in the first analysis were also found to beassociated with RMI in the second analysis (see Table 9).

Additionally, genetic markers identified as associated with acutecoronary events or response to statin treatment for the prevention ofcoronary events in the CARE samples were also genotyped in a secondsample set, the West of Scotland Coronary Prevention Study (WOSCOPS)sample set. The design of the original WOSCOPS cohort and the nestedcase-control study have been described (Shepherd et. al, N. Eng. J.Med., November 16: 333 (20), pp. 1301-7 1995; Packard et. al. N. Eng. J.Med., October 19: 343 (16), pp. 1148-55, 2000). The objective of theWOSCOPS trial was to assess pravastatin efficacy at reducing risk ofprimary MI or coronary death among Scottish men withhypercholesterolemia (fasting LDL cholesterol >155 mg/dl). Participantsin the WOSCOPS study were 45-64 years of age and followed for an averageof 4.9 years for coronary events. The nested case-control study includedas cases all WOSCOPS patients who experienced a coronary event(confirmed nonfatal MI, death from coronary heart disease, or arevascularization procedure; N=580). Controls were 1160 age and smokingstatus-matched unaffected patients. All individuals included in thestudy had signed a written informed consent form and the study protocolwas approved by IRBs. DNA was extracted and genotyped as describedabove.

Statistical Analysis for Association of SNPs with Specific ClinicalEndpoints

Qualitative phenotypes of the patients who were genotyped (Table 6) wereanalyzed using an overall logistic regression model that included anintercept, a parameter for the effect of a genotype containing two rarealleles versus a genotype containing no rare alleles, and a parameterfor the effect of a genotype containing one rare allele versus agenotype containing no rare alleles. The test of the overall model is achi-square test with five degrees of freedom for analyses containing allthree genotypes, and four degrees of freedom for analyses containing twogenotypes. An example of a SNP associated with increased risk for RMI ishCV529710 (Table 6). hCV529710 is strongly associated with Fatal CHD(Coronary Heart Disease)/Non-fatal MI and Fatal AtheroscleroticCardiovascular Disease (Relative Risk=1.5 and 2.3, and p-values <0.05and <0.005, respectively.

Quantitative phenotypes of the patients who were genotyped (Table 7)were also analyzed using an overall generalized linear model (GLM) thatincluded an intercept, a parameter for the effect of a genotypecontaining two rare alleles, and a parameter for the effect of agenotype containing one rare allele. The test of the overall GLM modelis an F-test.

Effect sizes for association of SNPs with endpoints were estimatedthrough odds ratios in placebo treated patients only, separately forcarriers of each genotype (groups of 0, 1, and 2 minor allele carriers).The effect was considered to be significant if the p-value for testingwhether any of the SNP genotype parameters in overall model was <0.05.An example of a SNP associated with increased risk for a quantitativephenotype such as very low density lipoproteins (VLDL) is hCV22274624with a p value <0.0005.

Statistical analysis for association of SNPs with pravastatin treatmentin cardiovascular events prevention (Table 8) was carried out using anoverall logistic regression model that included an intercept, aparameter for the effect of a genotype containing two rare allelesversus a genotype containing no rare alleles, a parameter for the effectof a genotype containing one rare allele versus a genotype containing norare alleles, a parameter for the effect of use of pravastatin versusthe use of placebo, and parameters for the interaction effects betweenSNP genotypes and pravastatin use. The test of the overall model is achi-square test with two degrees of freedom for analyses containing allthree genotypes, and one degree of freedom for analyses containing twogenotypes.

Effect sizes were estimated through odds ratios (pravastatin groupversus placebo) for carriers of each genotype (groups of 0, 1, and 2minor allele carriers). The effect was considered to be significant ifp-value for testing whether any of the interactions between SNPgenotypes and pravastatin use were <0.05. An example of a SNP associatedwith a response to statin treatment in preventing an adverse coronaryevent is hCV2741051. When the pravastatin group is compared to thecontrol group, individuals with one or two of the rare alleles had oddsratios of 0.43 and 0.26 respectively with a p-value of <0.05. Thisparticular SNP is also associated with a reduced risk of stroke in thepravastatin treated group when one or two rare alleles are present in apatient (odds rations of 0.21 and 0.23 p<0.05). Odds ratios less thanone indicate that the specific SNP allele has a protective effect andodds ratios greater than one indicate that the specific SNP allele hasan adverse effect.

Statistical analysis for the association of SNPs with RMI or stroke(Table 9) was also carried out using stepwise logistic regression.Relative risk (RR) and 95% confidence intervals (CI)s—5-6 years relativerisk of a RMI event or stroke given the SNP genotype were calculated bythe Wald test. Certain SNPs show association of SNPs with adversecoronary events such as RMI and stroke in CARE samples. This associationof certain SNPs with adverse coronary events could also be replicated bycomparing associations observed in the first analysis of the CAREsamples and the second analysis of the CARE samples (see above). Anexample of SNPs associated with increased risk for RMI are hCV517658 andhCV 8722981 with RR of 1.34 and 2.01 respectively. RR values <1 areassociated with a reduced risk of the indicated outcome and RR values >1are associated with an increased risk of the indicated outcome. Anexample of a SNP associated with decreased risk for RMI that replicatedbetween the first and second analysis of the CARE data is hCV761961 thathad ORs of 0.5 and 0.5 in the first and second analyses respectively. Anexample of a SNP associated with increased risk for RMI that replicatedin the first and second analyses is hCV8851080 that had ORs of 2.7 and1.9 in the first and second analyses respectively. An example of a SNPassociated with increased risk for stroke that replicated in the firstand second analyses of the CARE data is hCV11482766 that had ORs of 3.5and 3.3 in the first and second analyses respectively.

For statistical analysis of association of SNPs with pravastatintreatment in RMI prevention (Table 10), effect sizes were estimatedthrough genotypic RR, including 95% CIs. Homogeneity ofCochran-Mantel-Haenszel odds ratios was tested across pravastatin andplacebo strata using the Wald test. A SNP was considered to have asignificant association with response to pravastatin treatment if itexhibited Wald p-value <0.05 in the allelic association test or in anyof the 3 genotypic tests (dominant, recessive, additive). Table 10 showsassociation of SNPs predictive of statin response with cardiovascularevents prevention under statin treatment, with an adjustment forconventional risk factors such as age, sex, smoking status, baselineglucose levels, BMI, history of hypertension, etc. (this adjustmentsupports independence of the SNP association from conventional riskfactors). This table also provides the frequency data for the at riskallele in the columns labeled “Case Y PRIMER ALLELE NucleotideFrequency” and “Control Y PRIMER ALLELE Nucleotide Frequency”. Allelefrequencies for the cases and controls ≤0.49 indicate that the at-riskallele is the minor allele. Allele frequencies ≥0.50 indicate that theat-risk allele is the major allele. An example of a SNP associated withincreased risk for an adverse cardiovascular event in the placebo groupusing a dominant genotypic test is hCV25644901. The dominant genotype(GG or GA) had a RR of 1.92 of being associated with an adversecardiovascular event in the placebo group. However, this same SNP wasprotective in the statin treated group with a RR of 0.58. An example ofa SNP associated with an adverse cardiovascular event in the placebogroup using the allelic association test is hCV16044337 with a RR of1.87 for the homozygous AA genotype. This same genotype was protectivein the statin treated group with a RR of 0.56.

The statistical results provided in Table 11 demonstrate association ofa SNP in the CD6 gene (hCV2553030) that is predictive of statin responsein the prevention of RMI, justified as a significant difference in riskassociated with the SNP between placebo and statin treated strata(Breslow Day p-values <0.05). Table 11 presents the results observed insamples taken from both the CARE and WOSCOP studies. In both studies theindividuals homozygous for the minor allele were statistically differentfrom heterozygous and major allele homozygous individuals in thepravastatin treated group vs. the placebo treated group. This SNP wasassociated with a reduced risk of an adverse coronary event in the CAREand WOSCOPS studies with RR or OR of 0.13 and 0.23 respectively in thetwo studies. Therefore, SNPs identified as useful for predicting RMI mayalso be useful for predicting increased risk for developing primary MI.

Table 12 shows the association of a SNP in the FCAR gene (hCV7841642)that is predictive of MI risk and response to statin treatment.Individuals who participated in both the CARE and WOSCOPS studies, whodid not receive pravastatin treatment and who were heterozygous orhomozygous for the major allele (AG or GG) (OR of 1.58, 1.52, 1.5, 1.47in the respective studies) had a significantly higher risk of having anMI vs. individuals who were homozygous for the minor allele. However,individuals in the CARE study who were heterozygous or homozygous forthe FCAR major allele were also statistically significantly protected bypravastatin treatment against an adverse coronary event relative to theindividuals homozygous for the minor allele (OR 0.31, 0.79). Therefore,an allele found to be associated with risk for MI, RMI, stroke, or otheradverse cardiovascular event, may also be useful for predictingresponsiveness to statin treatment. SNPs associated with treatmentresponse to pravastatin may also be predictive of responsiveness of anindividual to other statins as a class.

The data presented in Table 8 based on an association of genotypes withpravastatin efficacy of the CARE samples were further analyzed andpresented in Table 13. The further analysis was performed to align thedata obtained from the analysis of the CARE samples, which was aprospective study, to the analysis of the WOSCOP samples, which was acase/control study. Table 13 also presents an analysis of theassociation of genotypes with pravastatin efficacy in the WOSCOPssamples. Relative to the analysis performed on the data presented inTable 8, there are two significant differences to determine if the SNPinfluenced pravastatin efficacy. Data obtained from the CARE sampleswere separated by study design into two groups, those in the prospectivestudy design group and those in the case/control study design group. Theoriginal care study contained 16 protocol defined cardiovascular diseasedefined endpoints and 150 other phenotypes. The prospective study designpresented in Table 13 only looks at two possible end points, thoseindividuals who had a fatal MI, sudden death, or a definite non-fatalMI, or those individuals who had a fatal or non-fatal MI (probable ordefinite). In the case/control study design, in addition to only lookingat cases that fell into the two possible endpoints defined above, caseswere only compared to matched controls, ie. controls matched by age,smoking status and did not have any adverse coronary events or died dueto other causes. The control groups used to compare the data were alsodivided into two groups, the “all possible” control group and the“cleaner” control group. The all possible control group consists of allof the controls that were white males and were matched for age andsmoking status but had any disease outcome. The cleaner control groupwere also matched for age and smoking status but were further restrictedto only those individuals that had MI as an outcome. Because theparticipants in the WOSCOPs trial were all white males, only dataobtained from white males in the CARE study were analysed. Data from the“all possible” and “cleaner” controls were compared to data obtainedfrom the cases in the prospective study design while only data from“cleaner” controls were compared to cases in the case/control studydesign. The data from the case/control cohorts were analysed usingconditional logistic regression (as opposed to logistic regression usedfor the original analysis).

An example of a SNP associated with fatal MI/sudden death/non-fatal MIusing data from the CARE study is hCV2442143. Patients with 0 rarealleles (or patients homozygous for the dominant allele) had an OR of0.42 of being associated with the adverse outcome in the presence ofstatin treatment. Patients with one or two rare alleles had ORs of 0.78and 1.16 respectively of being associated with the adverse outcome.However the 95% CI for these two genotypes makes the result notstatistically significant.

The data presented in Table 6 based on an association of genotypes withadverse cardiovascular outcomes such as fatal or non-fatal MI werefurther analyzed and presented in Table 14. Similar to the datapresented in Table 13, the analysis was modified to align the dataobtained from the CARE samples to data obtained from the WOSCOPssamples. In addition, Table 14 also presents an analysis of theassociation of genotypes with adverse cardiovascular outcomes observedin the WOSCOPs samples. As above, there are two significant differences.Data obtained from the CARE samples were separated by study design intoa prospective or a case/control study design group as defined above.Secondly, as above the control groups were divided into the all possiblecontrols and the cleaner controls. Controls were age matched for age andsmoking status with the cases. The all possible controls includeindividuals as defined above and the cleaner controls also useindividuals as defined above. As above, only data obtained from samplesfrom white males were analysed and are presented in Table 14.

An example of a SNP associated with an adverse cardiovascular event suchas a fatal MI or non-fatal MI using data from the CARE study ishCV529706. Patients with 2 rare alleles vs. 0 rare alleles had an OR of2.08 of having the adverse event (p,0.05). The statistical resultsprovided in Table 15 demonstrate the association of a SNP in the PON1gene(hCV2548962) with pravastatin efficacy in both the CARE and WOSCOPssample sets. The analysis was refined as described for both Tables 13and 14. The data show that patients with 2 rare alleles weresignificantly protected against a fatal or non-fatal MI when treatedwith pravastatin (ORs 0.28-0.34, p<0.05).

Example 2: Statistical Analysis of SNP Combinations Associated with RMIand Predictive of Response to Statin Treatment

Multiple markers were identified in the CARE study as associated withthe ability of a patient to respond to statin treatment by having areduced risk of RMI (specifically see Tables 8 and 10). The datapresented in those Tables, especially Table 10 indicate that the minoralleles of NPC1 (hCV25472673) and HSPG2 (hCV1603656) and the majorallele of ABCA1 (hCV2741051) are protective against RMI in patients thatreceive statin treatment. The data also show that certain genotypes ofthe alleles identified in Table 10 are protective against RMI inpatients that receive statin treatment. The homozygous minor allele orthe heterozygous minor and major allele of the NPC1 gene (CC, CT) andthe HSPG2 gene (TT, TC) are protective genotypes (low risk genotypes)against RMI in patients that receive statin treatment. The homozygousmajor allele of the ABCA1 gene (CC) is a protective genotype (low riskgenotype) in patients that receive statin treatment.

The genotype data generated from the DNA of patients who participated inthe CARE study was analyzed to determine the effect that pravastatintreatment had on the occurrence of RMI in patients with each of thepotential genotypes (low risk, protective or high risk, non-protective)for the ABCA1 gene, the NPC1 gene and the HSPG1 gene independently. Thedata are presented in Table 16.

TABLE 16 Age-Adjusted pravastatin effect (by genotype group) N Label RR95% CI p-value 1366 High risk ABCA1 0.9567 0.6709 1.3644 0.807 genotype1441 Low risk ABCA1 0.5883 0.4249 0.8145 0.0014 genotype Total = 28071045 High risk NPC1 1.0824 0.7265 1.6127 0.6971 genotype 1755 Low riskNPC1 0.5938 0.4388 0.8035 0.0007 genotype Total = 2800 2375 High riskHSPG2 0.8097 0.6271 1.0453 0.1053 genotype  428 Low risk HSPG2 0.39340.2002 0.7729 0.0068 genotype Total = 2803The data show that the low risk genotypes of the ABCA1 gene, the NPC1gene and the HSPG2 gene are protective against RMI in patients that havereceived statin treatment.

The effect of pravastatin treatment on the occurrence of RMI in patientswith each of the potential genotypes (protective, low risk genotype ornon-protective, high risk genotype) for each of the ABCA1 gene, NPC1gene, and HSPG2 gene alone, and combinations with the other two genesthereof are presented in Table 17.

TABLE 17 Age-adjusted pravastatin effect (by genotype group) N Label RR95% CI p-value 436 High risk, non-protective genotypes 1.7175 0.8773.3637 0.1148 447 Low risk, protective ABCA1 only 0.8765 0.4848 1.58480.6627 701 Low risk, protective NPC1 only 0.8954 0.5543 1.4462 0.6514 83Low risk, protective HSPG2 only 0.2487 0.0304 2.0372 0.1947 784 Low riskABCA1 and NPC1 only 0.5258 0.3343 0.8271 0.0054 (pattern 2 genotype) 77Low risk ABCA1 and HSPG2 only 1.0054 0.2593 3.8982 0.9938 144 Low riskNPC1 and HSPG2 only 0.2964 0.0652 1.3482 0.1156 122 Low risk ABCA1, NPC1and HSPG2 0.2399 0.0704 0.8177 0.0225 (pattern 3 genotype) Total = 2794The data show that patients that have a combination of the ABCA1 andNPC1 low risk genotypes (pattern 2) or patients that have a combinationof the ABCA1, NPC1 and the HSPG2 low risk genotypes (pattern 3) have asignificantly reduced risk of RMI if they receive pravastatin treatmentrelative to those patients who received placebo.

Patients in the CARE trial that had a high risk, non-protective genotypefor the ABCA1 gene, the NPC1 gene and the HSPG2 gene, had the low riskABCA1 genotype only, had the low risk ABCA1 and HSPG2 genotypes only,had the low risk NPC1 genotype only, had the low risk HSPG2 genotypeonly, or had the low risk NPC1 and HSPG1 genotype are collectivelycalled pattern 0 patients. Patients in the CARE trial that had thepattern 0 genotype and received placebo had a 5 year risk of a RMI of8.1%. Patients in the trial that had the pattern 2 genotype and receivedplacebo had a 5 year risk of a RMI of 12.5%, or a 64% increase overthose patients that had the pattern 0 genotypes. Patients in the trialthat had the pattern 3 genotype and received placebo had a 5 year riskof a RMI of 19.3% or a 138% increase over those patients that had thepattern 0 genotypes. These data show that patients that do not receivestatin treatment and have the pattern 2 or the pattern 3 genotypes havea 64% or a 138% increased risk of a RMI in a 5 year period over patientswith a pattern 0 genotype (LogRank p-value=0.0013).

Patients in the CARE trial with pattern 0 genotypes who did not receivestatin treatment had a 5 year risk of a RMI of 8.1%. Patients in theCARE trial with pattern 0 genotypes who did receive pravastatintreatment had a 5 year risk of a RMI of 7.9% (N=1888, 67.6% of the CAREpopulation, LogRank p-value=0.9345). Patients in the trial with pattern2 genotypes, who did not receive statin treatment had a 5 year risk of aRMI of 12.5%. Patients in the trial with pattern 2 genotypes who didreceive pravastatin treatment had a 5 year risk of a RMI of 6.8%(HR=0.53, 95% CI: 0.33-0.85, p=0.0081, N=784, 28.1% of the CAREpopulation). This is a 50% reduction in risk over a 5 year period forRMI. Patients in the trial with pattern the 3 genotype, who did notreceive statin treatment had a 5 year risk of a RMI of 19.3%. Patientsin the trial with the pattern 3 genotype who did receive pravastatin hada 5 year risk of a RMI of 4.6% (HR=0.2, 95% CI=0.06-0.8, p=0209, N=122,4.4% of the CARE population). This is an 80% reduction in risk over a 5year period for RMI. These data are summarized in Table 18.

TABLE 18 RMI No RMI Risk RR_(Statin) RD_(Statin) All Pravastatin 1061367 0.072 0.76 0.023 Placebo 137 1303 0.095 Pattern 0 Pravastatin 78906 0.079 0.98 0.001 Placebo 73 831 0.081 Pattern 2 Pravastatin 25 3420.068 0.55 0.057 Placebo 52 365 0.125 Pattern 3 Pravastatin 3 62 0.0460.24 0.147 Placebo 11 46 0.193

Measures of prognostic value were calculated from the above data. Thepositive predictive value (PPV) of each genotype pattern can becalculated by dividing the number of individuals with that genotype whoreceived placebo and had a RMI by the total number of individuals whohad that genotype and received placebo. The PPV of the pattern 3genotype is 19.3% and the PPV of the pattern 2 genotype is 12.5%. Thenegative predictive value (NPV) of each genotype can be calculated bydividing the total number of individuals who had those genotypes,received placebo and did not have a RMI by the total number ofindividuals who had that genotype and received placebo. The NPV ofpattern 0 is 91.9%. From these calculations, the entire population canbe broken down into different absolute risk groups. The over all risk ofthe population to have a RMI after having an MI is 9.5%. However, forindividuals with the pattern 0 genotype, the risk of a RMI is reduced to8.1%. Individuals with pattern 2 and pattern 3 genotypes have a 12.5%and 19.3% risk of a RMI.

All publications and patents cited in this specification are hereinincorporated by reference in their entirety. Various modifications andvariations of the described compositions, methods and systems of theinvention will be apparent to those skilled in the art without departingfrom the scope and spirit of the invention. Although the invention hasbeen described in connection with specific preferred embodiments andcertain working examples, it should be understood that the invention asclaimed should not be unduly limited to such specific embodiments.Indeed, various modifications of the above-described modes for carryingout the invention that are obvious to those skilled in the field ofmolecular biology, genetics and related fields are intended to be withinthe scope of the following claims.

TABLE 5 Al- Sequence A Sequence B Sequence C Marker leles(allele-specific primer) (allele-specific primer) (common primer)hCV1085600 C/G AGCTGTTCGTGTTCTATGATC AGCTGTTCGTGTTCTATGATGGAAGTCAACAGTGAACATGTGA (SEQ ID NO: 85091) (SEQ ID NO: 85092)(SEQ ID NO: 85093) hCV1088055 A/G CACTCACACTGGGGAAGA ACTCACACTGGGGAAGGCCTTCCAGGTGAAGGTCAC (SEQ ID NO: 85094) (SEQ ID NO: 85095)(SEQ ID NO: 85096) hCV11225994 A/G TCCCAATCCCAGGACA CCCAATCCCAGGACGTGACATTGCACTCTCAAATATTT (SEQ ID NO: 85097) (SEQ ID NO: 85098)(SEQ ID NO: 85099) hCV11359098 C/G CAAAATGTAGAAGGTTCATATGAGCAAAATGTAGAAGGTTCATATGAC GAGCTGTGTGTTTCTTTGTTCTA (SEQ ID NO: 85100)(SEQ ID NO: 85101) (SEQ ID NO: 85102) hCV11482766 C/T GCGCACCCAGGTCAGGCGCACCCAGGTCAA CCACGTTCTGGTCGATCTT (SEQ ID NO: 85103)(SEQ ID NO: 85104) (SEQ ID NO: 85105) hCV11571465 C/G GCTGGAGTTCATGTCGCGCTGGAGTTCATGTCGG CCTTGGCTGTGTGGTACAG (SEQ ID NO: 85106)(SEQ ID NO: 85107) (SEQ ID NO: 85108) hCV11696920 A/GGTCTTTAGAAGCCTCTTCAGAATA CTTTAGAAGCCTCTTCAGAATG CGGCTTTGGCCTACAAG(SEQ ID NO: 85109) (SEQ ID NO: 85110) (SEQ ID NO: 85111) hCV1180648 G/AGGGTAAAATTCAGTAAGGTTGG AGGGTAAAATTCAGTAAGGTTGA TCGCTATCCAAGTGAACATATC(SEQ ID NO: 85112) (SEQ ID NO: 85113) (SEQ ID NO: 85114) hCV11852251 C/GGGCTGTTGTCTCACCCTC GGCTGTTGTCTCACCCTG TGTCATCAGATGAAGAAGAGAGAA(SEQ ID NO: 85115) (SEQ ID NO: 85116) (SEQ ID NO: 85117) hCV11889257 A/GCTCTCTTTCTAGAAACTGAA TCTCTTTCTAGAAACTGAA GGGCAGGGCTAGGAGTAG GAAATTGAAATC (SEQ ID NO: 85120) (SEQ ID NO: 85118) (SEQ ID NO: 85119)hCV11942529 C/T ACTGTCACCTGTTGGGG GACTGTCACCTGTTGGGA CCAGGGTTGGGCTACTG(SEQ ID NO: 85121) (SEQ ID NO: 85122) (SEQ ID NO: 85123) hCV11951095 T/CCGTGACCCTGCCGT CGTGACCCTGCCGC GGGCCAGCATGTGGAC (SEQ ID NO: 85124)(SEQ ID NO: 85125) (SEQ ID NO: 85126) hCV11975296 T/CCAGTCCATGGTTCCTTCAT CAGTCCATGGTTCCTTCAC CTCCACCTGCATTTCAGAG(SEQ ID NO: 85127) (SEQ ID NO: 85128) (SEQ ID NO: 85129) hCV12020339 G/TGGACCCCCGAAGGC TGGACCCCCGAAGGA GGCCCCAACAGTTGACTG (SEQ ID NO: 85130)(SEQ ID NO: 85131) (SEQ ID NO: 85132) hCV1202883 A/G GCGTGATGATGAAATCGAGCGTGATGATGAAATCGG AGCCTCTCCTGACTGTCATC (SEQ ID NO: 85133)(SEQ ID NO: 85134) (SEQ ID NO: 85135) hCV1207994 A/C GCAGCAGTCGCCCTTGCAGCAGTCGCCCTG CATTTTGCTGATGTTTGTTTCTAG (SEQ ID NO: 85136)(SEQ ID NO: 85137) (SEQ ID NO: 85138) hCV12102850 C/T GGTTACAGGCTCCAGGACGGTTACAGGCTCCAGGAT CTGATGGCCAAAAGAAGAGT (SEQ ID NO: 85139)(SEQ ID NO: 85140) (SEQ ID NO: 85141) hCV12108245 A/G GCCCTACAGCGGGTCCTACAGCGGGC GACGGATCTGACAGAATCTTTC (SEQ ID NO: 85142)(SEQ ID NO: 85143) (SEQ ID NO: 85144) hCV12114319 A/G GACACTGCCCTCATCGTCACTGCCCTCATCGC CCTGTCCTTGAGGTCTGATC (SEQ ID NO: 85145)(SEQ ID NO: 85146) (SEQ ID NO: 85147) hCV12120554 C/TACTGTCCTGTCTCTCCTCG GACTGTCCTGTCTCTCCTCA TTGCCAGCCATGACTAGA(SEQ ID NO: 85148) (SEQ ID NO: 85149) (SEQ ID NO: 85150) hCV1253630 A/GTCGCAGGTGTCCCTA CGCAGGTGTCCCTG CCCCATCCCTTCTCA (SEQ ID NO: 85151)(SEQ ID NO: 85152) (SEQ ID NO: 85153) hCV1260328 A/G TCCACGTGGACCAGGTCCACGTGGACCAGGC GCCCAGGTATTTCATCAGC (SEQ ID NO: 85154)(SEQ ID NO: 85155) (SEQ ID NO: 85156) hCV1345898 C/TCAGTTTTCCATGGGTTCTACTAC CAGTTTTCCATGGGTTCTACTATTTATGAAATGGTACAGACAAGTGAT (SEQ ID NO: 85157) (SEQ ID NO: 85158)(SEQ ID NO: 85159) hCV1345898 T/C CAGTTTTCCATGGGTTCTACTATCAGTTTTCCATGGGTTCTACTAC TTATGAAATGGTACAGACAAGTGAT (SEQ ID NO: 85160)(SEQ ID NO: 85161) (SEQ ID NO: 85162) hCV1361979 A/GCCAGTTTTGGTGTCAACTAGAAA CCAGTTTTGGTGTCAACTAGAAG TTGCAACCTGAAAAACATAACTA(SEQ ID NO: 85163) (SEQ ID NO: 85164) (SEQ ID NO: 85165) hCV1366366 A/GTCCCTTAGTCCGGATGAT TCCCTTAGTCCGGATGAC GACTCTTTTGCAGGAATGTGT(SEQ ID NO: 85166) (SEQ ID NO: 85167) (SEQ ID NO: 85168) hCV1376137 A/GCTCCATCATTGCAGACCA TCCATCATTGCAGACCG CCAATTCCCCTGATGTTAAA(SEQ ID NO: 85169) (SEQ ID NO: 85170) (SEQ ID NO: 85171) hCV1403468 A/CACTGGCCCCTTGCAT ACTGGCCCCTTGCAG AGGAGGGAACCAAACCTTA (SEQ ID NO: 85172)(SEQ ID NO: 85173) (SEQ ID NO: 85174) hCV1466546 A/G TCTGGCTTCCGGGAATCTGGCTTCCGGGAG CGTAGCTGTTGACCATCATTTA (SEQ ID NO: 85175)(SEQ ID NO: 85176) (SEQ ID NO: 85177) hCV15757745 C/GAGATTTTCACCCATCCATG GAGATTTTCACCCATCCATC TGCCGACTCAGAAACTCTCTA(SEQ ID NO: 85178) (SEQ ID NO: 85179) (SEQ ID NO: 85180) hCV15760070 A/TTGTCCAGATCCACATAGAACA TTGTCCAGATCCACATAGAACT CTTTATGCAGCGGACCAT(SEQ ID NO: 85181) (SEQ ID NO: 85182) (SEQ ID NO: 85183) hCV15852235 C/TAAGAGGTCCTGAATCTTCTCTC AAGAGGTCCTGAATCTTCTCTT ATGAAATGGGTCAACAAAACT(SEQ ID NO: 85184) (SEQ ID NO: 85185) (SEQ ID NO: 85186) hCV15871020 G/AATGTGAACTTAGCACTTTTATCAG ATGTGAACTTAGCACTTTTATCAA AACCTTCCGTGGAAAGAGA(SEQ ID NO: 85187) (SEQ ID NO: 85188) (SEQ ID NO: 85189) hCV15876071 G/ACGACTTAAGGGTGTAGTGTGAC CGACTTAAGGGTGTAGTGTGAT CCGAAAACGGAAGCATC(SEQ ID NO: 85190) (SEQ ID NO: 85191) (SEQ ID NO: 85192) hCV15882348 C/TGCTGCTCTGCGCCG GCTGCTCTGCGCCA GCCCTCTGCGTACCTAAGG (SEQ ID NO: 85193)(SEQ ID NO: 85194) (SEQ ID NO: 85195) hCV15943710 A/G CCTCATGGAGATCTTTCACCTCATGGAGATCTTTCG GAGGCCAGCGAGGAGA (SEQ ID NO: 85196)(SEQ ID NO: 85197) (SEQ ID NO: 85198) hCV15954277 A/G TGTCGGTAAACATGGCAGTCGGTAAACATGGCG GGTGGGTGGTCTGACTCTC (SEQ ID NO: 85199)(SEQ ID NO: 85200) (SEQ ID NO: 85201) hCV15962586 C/T GGCTGTGCCTGGGACGGCTGTGCCTGGGAT GAAGGCAGGGACTTTTATCA (SEQ ID NO: 85202)(SEQ ID NO: 85203) (SEQ ID NO: 85204) hCV1603656 C/T GCTGCCCTCAGTCCGTGCTGCCCTCAGTCCA GGGCACTGCCAATTCTTAG (SEQ ID NO: 85205)(SEQ ID NO: 85206) (SEQ ID NO: 85207) hCV1603692 C/T GGCCTCTAGGGGGCCAGGCCTCTAGGGGGCT CCCCATTTGCACACAGAC (SEQ ID NO: 85208)(SEQ ID NO: 85209) (SEQ ID NO: 85210) hCV1603697 C/T CGGCCTGCGTGGACCGGCCTGCGTGGAT GCCCAGGGCGTGTTCT (SEQ ID NO: 85211) (SEQ ID NO: 85212)(SEQ ID NO: 85213) hCV16044337 A/G TCCGGGTGCACGTATA CGGGTGCACGTATGTGGAGAGTGTTTGCTCATCTAC (SEQ ID NO: 85214) (SEQ ID NO: 85215)(SEQ ID NO: 85216) hCV16047108 A/G TGTTTTCATCCACTTGAACTGTTTTTCATCCACTTGAACTGC CAATTTTGGCTCCCTTAAAAG (SEQ ID NO: 85217)(SEQ ID NO: 85218) (SEQ ID NO: 85219) hCV16053900 G/T GGACGTGCTCCAGGATGGGACGTGCTCCAGGATT GGTTCACATTTTGGTTCACAA (SEQ ID NO: 85220)(SEQ ID NO: 85221) (SEQ ID NO: 85222) hCV16165996 C/T CTGAGGCCTATGTCCTCCTGAGGCCTATGTCCTT AGCTCTCCTTTGTTGCTACTG (SEQ ID NO: 85223)(SEQ ID NO: 85224) (SEQ ID NO: 85225) hCV16166043 A/G CGGTTGAAGTCCTTGATCGGTTGAAGTCCTTGAC GGTTGTGCAGAGACATCTGA (SEQ ID NO: 85226)(SEQ ID NO: 85227) (SEQ ID NO: 85228) hCV16170435 G/CATCTCACAAATGATCGCTATG AATCTCACAAATGATCGCTATC CAGGCTCCATCTCACAGATAC(SEQ ID NO: 85229) (SEQ ID NO: 85230) (SEQ ID NO: 85231) hCV16170900 A/GCGCACACCAGGTTCTCAT CGCACACCAGGTTCTCAC GCAACTACCTGGGCCACTATA(SEQ ID NO: 85232) (SEQ ID NO: 85233) (SEQ ID NO: 85234) hCV16170911 T/CGGTTTCATTGCATGGTTTCT GTTTCATTGCATGGTTTCC GGGTACTGAATTTTTAAAAGGTTTTA(SEQ ID NO: 85235) (SEQ ID NO: 85236) (SEQ ID NO: 85237) hCV16170982 C/GCCCCCACTCTCCAGC CCCCCACTCTCCAGG GGCAAAAGCACTGTGAAGA (SEQ ID NO: 85238)(SEQ ID NO: 85239) (SEQ ID NO: 85240) hCV16172087 A/C GACTGCCCGTCAGCAGACTGCCCGTCAGCC GGAGGTCAGGTGGATGTTTA (SEQ ID NO: 85241)(SEQ ID NO: 85242) (SEQ ID NO: 85243) hCV16172249 C/GACTGTAATTTTTTTAAAGGTCCTG ACTGTAATTTTTTTAAAGGTCCTCGGATGTATATCATCTATCTTCACAGT (SEQ ID NO: 85244) (SEQ ID NO: 85245) ATAT(SEQ ID NO: 85246) hCV16172339 A/T CTGCGGCTCCACCT TGCGGCTCCACCATGGCATCTGCCATACTCA (SEQ ID NO: 85247) (SEQ ID NO: 85248)(SEQ ID NO: 85249) hCV16172571 A/G GGTACCATGGACTGTACTCACTGTACCATGGACTGTACTCACC AGGTTGGTTCTGGAGATGAC (SEQ ID NO: 85250)(SEQ ID NO: 85251) (SEQ ID NO: 85252) hCV16179493 C/T GGGTCCGGCCACACGGGTCCGGCCACAT GGGCCCCTCAGTGAAG (SEQ ID NO: 85253) (SEQ ID NO: 85254)(SEQ ID NO: 85255) hCV16182835 A/G TGTTCTTCCTTATGATGATGTGTTCTTCCTTATGATGATGC GGCGTTCCTCTCACCTTAATA (SEQ ID NO: 85256)(SEQ ID NO: 85257) (SEQ ID NO: 85258) hCV16189421 C/TGCCATCATTTGCTTCTAACAC GCCATCATTTGCTTCTAACAT GCTTATTTGCCAGAAAACATTT(SEQ ID NO: 85259) (SEQ ID NO: 85260) (SEQ ID NO: 85261) hCV16190893 C/TGCAGTACTTGCTTAGGG CGCAGTACTTGCTTAGGA GCCACCTTTATTTCTTTAGTGAA(SEQ ID NO: 85262) (SEQ ID NO: 85263) (SEQ ID NO: 85264) hCV16192174 G/AGAGCACCTTAACTATAGATGGTG TGAGCACCTTAACTATAGATGGTA CTTGTCAAGGCACAGAATAATT(SEQ ID NO: 85265) (SEQ ID NO: 85266) (SEQ ID NO: 85267) hCV16196014 C/GTGAAGAAGCTAAGGATTGAGG TGAAGAAGCTAAGGATTGAGC CTCTCCCTGGCTGAGTTG(SEQ ID NO: 85268) (SEQ ID NO: 85269) (SEQ ID NO: 85270) hCV16273460 C/TGCACTCTTGGACAAGCG TGCACTCTTGGACAAGCA AATGACATCCCCTATCTTTCTG(SEQ ID NO: 85271) (SEQ ID NO: 85272) (SEQ ID NO: 85273) hCV16276495 C/TGTACCTTCACCCATGGAAC GTACCTTCACCCATGGAAT TCACTTTCTGTTGATTACATGAGA(SEQ ID NO: 85274) (SEQ ID NO: 85275) (SEQ ID NO: 85276) hCV1647371 C/TCTGGCTGGGTCACTAACC GCTGGCTGGGTCACTAACT CCTCACCTGCATTCACATTT(SEQ ID NO: 85277) (SEQ ID NO: 85278) (SEQ ID NO: 85279) hCV1662671 A/GCAGCCAAGAGCAGGACA AGCCAAGAGCAGGACG CCCAAGACACGTTCAGAAAT(SEQ ID NO: 85280) (SEQ ID NO: 85281) (SEQ ID NO: 85282) hCV1789791 A/GACAGAATCAGGCAATATCCA CAGAATCAGGCAATATCCG TTTGTAGACCAGTGAAGAAGTGAT(SEQ ID NO: 85283) (SEQ ID NO: 85284) (SEQ ID NO: 85285) hCV1819516 C/TCCCCTGTTGAGGAGTATTG GCCCCTGTTGAGGAGTATTA GTTCTGCCAGGGAATCTCTA(SEQ ID NO: 85286) (SEQ ID NO: 85287) (SEQ ID NO: 85288) hCV1842400 A/GTTGGTACCTGGCTCTCT TGGTACCTGGCTCTCC AAACTTCTTAGGACAGAGTGATTAGA(SEQ ID NO: 85289) (SEQ ID NO: 85290) (SEQ ID NO: 85291) hCV190754 C/TTCAAGGCTTAATGCCACTC TCAAGGCTTAATGCCACTT CGTAAGTCTGTGATTTGTCAATACT(SEQ ID NO: 85292) (SEQ ID NO: 85293) (SEQ ID NO: 85294) hCV2038 G/ACACGGCGGTCATGTG CCACGGCGGTCATGTA GGTGGAGCTTGGTTTCTCA (SEQ ID NO: 85295)(SEQ ID NO: 85296) (SEQ ID NO: 85297) hCV2126249 C/TCAGGGGAGTAAAGGTGACTC CAGGGGAGTAAAGGTGACTT GCTCAGCCAGCCAGAAA(SEQ ID NO: 85298) (SEQ ID NO: 85299) (SEQ ID NO: 85300) hCV2188895 A/GAGAGAATGTTACCTCTCCTGA GAGAATGTTACCTCTCCTGG TTCTCCTGGGTCAGATTCTC(SEQ ID NO: 85301) (SEQ ID NO: 85302) (SEQ ID NO: 85303) hCV2200985 C/GGCGCACCAGCTTCAG GCGCACCAGCTTCAC TGTAATACATGATTTTCAGACACAC(SEQ ID NO: 85304) (SEQ ID NO: 85305) (SEQ ID NO: 85306) hCV22271841 C/TCATCACGGAGATCCACC ATCATCACGGAGATCCACT TCAGCTCCAAGGAGATTCTTAG(SEQ ID NO: 85307) (SEQ ID NO: 85308) (SEQ ID NO: 85309) hCV22272267 A/GCTGGCAGCGAATGTTAT CTGGCAGCGAATGTTAC CCTCTAGAAAGAAAATGGACTGTAT(SEQ ID NO: 85310) (SEQ ID NO: 85311) (SEQ ID NO: 85312) hCV22272997 G/AGCGGTAGCAGCAGCG GCGGTAGCAGCAGCA AGGCCCTCCTACCTTTTG (SEQ ID NO: 85313)(SEQ ID NO: 85314) (SEQ ID NO: 85315) hCV22273204 A/G TCAGCTTCTTCACTGCTACAGCTTCTTCACTGCTG GCTTTGATTTCCTACTCTGATTTTA (SEQ ID NO: 85316)(SEQ ID NO: 85317) (SEQ ID NO: 85318) hCV22274624 C/T CCCTACAGAGGATGTCAGCCCTACAGAGGATGTCAA CAGAGCCTCCCTTGTCAC (SEQ ID NO: 85319)(SEQ ID NO: 85320) (SEQ ID NO: 85321) hCV22274632 A/CTGAATGAGCATCCAAAAGAA TGAATGAGCATCCAAAAGAC GCAGCACGAAGCATTCAT(SEQ ID NO: 85322) (SEQ ID NO: 85323) (SEQ ID NO: 85324) hCV2351160 A/GCCACCAGTGGCTATCA CCACCAGTGGCTATCG GGCAAGCAGGCTTGAGAA (SEQ ID NO: 85325)(SEQ ID NO: 85326) (SEQ ID NO: 85327) hCV2442143 C/TATTTAAGCATCATAGCATACCAC ATTTAAGCATCATAGCATACCATTGGTACACCATAAATCTTGACTTAC (SEQ ID NO: 85328) (SEQ ID NO: 85329)(SEQ ID NO: 85330) hCV2485037 A/G TGCAAGAGGACTAAGCATGAGCAAGAGGACTAAGCATGG GCGGCCTTGCACTCA (SEQ ID NO: 85331)(SEQ ID NO: 85332) (SEQ ID NO: 85333) hCV2531086 A/G GCCCCCCTCTCTGAAGACCCCCCTCTCTGAAGG CCAGTTCGTGGTATGTTCATCT (SEQ ID NO: 85334)(SEQ ID NO: 85335) (SEQ ID NO: 85336) hCV2531431 A/G GCCAATGTGGCGGAGCCAATGTGGCGGG CCTGGACGACGGTTTCA (SEQ ID NO: 85337) (SEQ ID NO: 85338)(SEQ ID NO: 85339) hCV25472673 C/T TGGGCTCCATCCCAC TGGGCTCCATCCCATCCAATTCTTTTTCTTCTTTCAGTT (SEQ ID NO: 85340) (SEQ ID NO: 85341)(SEQ ID NO: 85342) hCV25473653 C/T CTCTAACATCACCGTGTACGCCTCTAACATCACCGTGTACA GAGCTCTGGGTCAGAACTGT (SEQ ID NO: 85343)(SEQ ID NO: 85344) (SEQ ID NO: 85345) hCV25474627 A/GGGTACCATGGACTGTACTCACT GTACCATGGACTGTACTCACC AGGTTGGTTCTGGAGATGAC(SEQ ID NO: 85346) (SEQ ID NO: 85347) (SEQ ID NO: 85348) hCV2548962 C/TCAAATACATCTCCCAGGATC CAAATACATCTCCCAGGATT GTTTTAATTGCAGTTTGAATGATAT(SEQ ID NO: 85349) (SEQ ID NO: 85350) (SEQ ID NO: 85351) hCV2553030 C/TCCGGCTTGCACTTCAC CCGGCTTGCACTTCAT CTTTGTGGCCGCAGTAGT (SEQ ID NO: 85352)(SEQ ID NO: 85353) (SEQ ID NO: 85354) hCV25593221 C/TGGCAACTCCTAGTAGTACAAC GGCAACTCCTAGTAGTACAAT GGAAGTTTCCATCCAAATTTAC(SEQ ID NO: 85355) (SEQ ID NO: 85356) (SEQ ID NO: 85357) hCV25598594 A/GATATATTGACCGTTCTCCCAT ATATATTGACCGTTCTCCCAC GCCACCTCCAACCATATC(SEQ ID NO: 85358) (SEQ ID NO: 85359) (SEQ ID NO: 85360) hCV25607108 A/GCCCTGTACTTTCATAAGATGCT CCTGTACTTTCATAAGATGCC ACGACGCCAAGGTGATA(SEQ ID NO: 85361) (SEQ ID NO: 85362) (SEQ ID NO: 85363) hCV25610470 A/GCACAATCACCACGGTCT ACAATCACCACGGTCC CCTTCTGCATCAGCATCTTC(SEQ ID NO: 85364) (SEQ ID NO: 85365) (SEQ ID NO: 85366) hCV25610774 C/TGGGTCGGTGCAAGAGG GGGTCGGTGCAAGAGA GCACCTTGGTGGGTTTGT (SEQ ID NO: 85367)(SEQ ID NO: 85368) (SEQ ID NO: 85369) hCV25610819 A/T GGACGTGGACATGGAGTGGACGTGGACATGGAGA CGGCGCTCGTAGGTG (SEQ ID NO: 85370) (SEQ ID NO: 85371)(SEQ ID NO: 85372) hCV25613493 C/T CGGCCCTCAGGACC CCGGCCCTCAGGACTGCGGAAGGTACCAAGTTTG (SEQ ID NO: 85373) (SEQ ID NO: 85374)(SEQ ID NO: 85375) hCV25614474 A/G CTGTTGTCCTGCTTCCAA CTGTTGTCCTGCTTCCAGGTTTCTGCATCAGTGAGATTTT (SEQ ID NO: 85376) (SEQ ID NO: 85377)(SEQ ID NO: 85378) hCV25615376 G/A ATTTAACACCACTATACTCTCAGATTTAACACCACTATACTCTCAA GGATATGCCTTCTTTGGAAATA (SEQ ID NO: 85379)(SEQ ID NO: 85380) (SEQ ID NO: 85381) hCV25615626 A/GAATATACCATTCTGTTAGGACTTA ATATACCATTCTGTTAGGACTTG GTGGTGGTGGGTCAGTATG(SEQ ID NO: 85382) (SEQ ID NO: 85383) (SEQ ID NO: 85384) hCV25617571 C/TCCAGCAGTATGGACG TGCCAGCAGTATGGACA CCATCCAGCCTCAGGAAC (SEQ ID NO: 85385)(SEQ ID NO: 85386) (SEQ ID NO: 85387) hCV25620145 A/GCACACCAGCAATGATGAAACT CACCAGCAATGATGAAACC GGGCTAACTCTTTGCATGTTC(SEQ ID NO: 85388) (SEQ ID NO: 85389) (SEQ ID NO: 85390) hCV25620774 C/TCACCCTGGCTGGAGAG CACCCTGGCTGGAGAA CTCCCTGTCCCAAAAAGAC (SEQ ID NO: 85391)(SEQ ID NO: 85392) (SEQ ID NO: 85393) hCV25623265 A/G TGGAGGCTGATGGGTAGGAGGCTGATGGGTG CGCTTTGCAGCCATAACT (SEQ ID NO: 85394) (SEQ ID NO: 85395)(SEQ ID NO: 85396) hCV25627634 C/G CACCCTGCAGATGGAAC CACCCTGCAGATGGAAGCAAGACTCCTTCATCCTCAATAGT (SEQ ID NO: 85397) (SEQ ID NO: 85398)(SEQ ID NO: 85399) hCV25629492 A/G CCCACAGCCTGCGAT CCCACAGCCTGCGACCCGCTTGAGGTCCACATA (SEQ ID NO: 85400) (SEQ ID NO: 85401)(SEQ ID NO: 85402) hCV25630499 C/T CATTGCTGGTTTCCACG CATTGCTGGTTTCCACAGGCAGTGGCACACAATCT (SEQ ID NO: 85403) (SEQ ID NO: 85404)(SEQ ID NO: 85405) hCV25630686 C/T AGGTTGTACCTGTAGCACTAAGTAGGTTGTACCTGTAGCACT TGGGCTCCTCAGAGAAAATAT AC AAGAT (SEQ ID NO: 85408)(SEQ ID NO: 85406) (SEQ ID NO: 85407) hCV25631989 C/TAAGATAAGCCTGTCACTGGTC AAGATAAGCCTGTCACTGGTT CAAGCCAGCCTAATAAACATAA(SEQ ID NO: 85409) (SEQ ID NO: 85410) (SEQ ID NO: 85411) hCV25637308 A/GCAGAAGGAAGACTACCATTAT CAGAAGGAAGACTACCATTAC CCTCCCCCTATTTATTTTTACAT(SEQ ID NO: 85412) (SEQ ID NO: 85413) (SEQ ID NO: 85414) hCV25637309 A/TGGCCACTTTGCCTGAATA GGCCACTTTGCCTGAATT CGAAATGTTCATTTTTAAAGTCAGA(SEQ ID NO: 85415) (SEQ ID NO: 85416) (SEQ ID NO: 85417) hCV25640505 A/GGATGCCCAGATTCCTAA GATGCCCAGATTCCTAG GCTCCATGCCTTGATTCT(SEQ ID NO: 85418) (SEQ ID NO: 85419) (SEQ ID NO: 85420) hCV25640926 A/GGCCCAGAGACAGGAAAAT GCCCAGAGACAGGAAAAC GCCTGCCCTCTGTTCA(SEQ ID NO: 85421) (SEQ ID NO: 85422) (SEQ ID NO: 85423) hCV25644901 A/GCAGACCTGCAGCTTCA AGACCTGCAGCTTCG TGTAACCCATCAACTCTGTTTATC(SEQ ID NO: 85424) (SEQ ID NO: 85425) (SEQ ID NO: 85426) hCV25651174 A/GCGCTGCAGGGTCAT CGCTGCAGGGTCAC CCTCCCCGCAGAGAATTA (SEQ ID NO: 85427)(SEQ ID NO: 85428) (SEQ ID NO: 85429) hCV25654217 C/GCCAATAGTCGTTTTTTGTTGG CCAATAGTCGTTTTTTGTTGC GCTGTGTGGGAAGTCAGAAC(SEQ ID NO: 85430) (SEQ ID NO: 85431) (SEQ ID NO: 85432) hCV25751017 C/ACTTATTTTCAGCGAAAGGC CCTTATTTTCAGCGAAAGGA CCAATGGTCGTCATCTCC(SEQ ID NO: 85433) (SEQ ID NO: 85434) (SEQ ID NO: 85435) hCV25761292 C/GGGGCAGCTCACCTCTCTAG GGGCAGCTCACCTCTCTAC GAGTGACTGCCAGAATTGTCT(SEQ ID NO: 85436) (SEQ ID NO: 85437) (SEQ ID NO: 85438) hCV25922320 A/GCTCGCAGCGGTCAGT TCGCAGCGGTCAGC GCTGGCGGGAATTTCT (SEQ ID NO: 85439)(SEQ ID NO: 85440) (SEQ ID NO: 85441) hCV25922816 A/G TGGCACTCAGGGCATTGGCACTCAGGGCAC CCAAAGAGGACTGACAACTGTA (SEQ ID NO: 85442)(SEQ ID NO: 85443) (SEQ ID NO: 85444) hCV25926178 C/GGCTTTATCAGAGACTCTGAAGC GCTTTATCAGAGACTCTGAAGG CCAAGGCCACGGATATC(SEQ ID NO: 85445) (SEQ ID NO: 85446) (SEQ ID NO: 85447) hCV25926771 C/TGGCCTTGGTCTCGC TGGCCTTGGTCTCGT TGCAGATCAGCTTGAAGAACTA (SEQ ID NO: 85448)(SEQ ID NO: 85449) (SEQ ID NO: 85450) hCV25930271 C/TGAATCTCATGTTCAGGAAATG CGAATCTCATGTTCAGGAAATA GCCATGGCCCATAAAAC(SEQ ID NO: 85451) (SEQ ID NO: 85452) (SEQ ID NO: 85453) hCV25942539 G/AGGATCCGACCGTTGAG GGATCCGACCGTTGAA TCATTTTGAACTCATTTTTTCTAGA(SEQ ID NO: 85454) (SEQ ID NO: 85455) (SEQ ID NO: 85456) hCV25943544 C/GATGTCCTGAAATACACGTATGAC ATGTCCTGAAATACACGTATGAG TCCCAACGTCAATTTCATATT(SEQ ID NO: 85457) (SEQ ID NO: 85458) (SEQ ID NO: 85459) hCV25956925 A/GGCTTCCCTGGGCTTCT CTTCCCTGGGCTTCC TGCTCATCATGAGTTTGAAACT(SEQ ID NO: 85460) (SEQ ID NO: 85461) (SEQ ID NO: 85462) hCV25990513 G/AAGATAATCATAAGCTGGAGAACAC AGATAATCATAAGCTGGAGAACATTGATTATGCATCTTCTGTCTTGTAG (SEQ ID NO: 85463) (SEQ ID NO: 85464)(SEQ ID NO: 85465) hCV2715953 C/G CATTGGGGCCAATGAC ATTGGGGCCAATGAGATGCATTTCATGTGAAAACTCT (SEQ ID NO: 85466) (SEQ ID NO: 85467)(SEQ ID NO: 85468) hCV2741051 C/T GCAGCCAGTTTCTCCC TGCAGCCAGTTTCTCCTCATGAAATGCTTCCAGGTATT (SEQ ID NO: 85469) (SEQ ID NO: 85470)(SEQ ID NO: 85471) hCV2741083 C/T GTTCCAACCAGAAGAGAATGGGTTCCAACCAGAAGAGAATA CTTGCCCCCAACAGTTAG (SEQ ID NO: 85472)(SEQ ID NO: 85473) (SEQ ID NO: 85474) hCV2769554 A/G TCCGTTGTTCTCAGGGATTCCGTTGTTCTCAGGGAC GGTTCCTGGAGGCATGTC (SEQ ID NO: 85475)(SEQ ID NO: 85476) (SEQ ID NO: 85477) hCV2782570 A/GCCAGCAAACTATGATGAATAAT CCAGCAAACTATGATGAATAAC TGGGATGACTCTAGCCACTTAC(SEQ ID NO: 85478) (SEQ ID NO: 85479) (SEQ ID NO: 85480) hCV2811372 A/GCAGCTGGACGACGAACA AGCTGGACGACGAACG CGGCTCTCCTTGATGAG (SEQ ID NO: 85481)(SEQ ID NO: 85482) (SEQ ID NO: 85483) hCV2983035 A/G TTGGACCCTCACATGAAATTGGACCCTCACATGAAG GCCATTTTCCACAATAAATATTT (SEQ ID NO: 85484)(SEQ ID NO: 85485) (SEQ ID NO: 85486) hCV2992252 T/C CCCTGTGATTGGCCATCCCTGTGATTGGCCAC CCTGCTCGCTCTGTCAC (SEQ ID NO: 85487) (SEQ ID NO: 85488)(SEQ ID NO: 85489) hCV3020386 G/T AGAATTGTGTCCAAAGAAGTTGAAGAATTGTGTCCAAAGAAGTTT AACTGGTATAATTTGAATCACAT (SEQ ID NO: 85490)(SEQ ID NO: 85491) AAAT (SEQ ID NO: 85492) hCV3023236 A/GCAGTTGGTTTTGTGGT AGTTGGTTTTGTGGC TGCTTCGTGGAGGTCAAT (SEQ ID NO: 85493)(SEQ ID NO: 85494) (SEQ ID NO: 85495) hCV3026206 C/G CCGTCTGGTAATTGTCCACCCGTCTGGTAATTGTCCAG TCAAGCCCTTGGCTAAGA (SEQ ID NO: 85496)(SEQ ID NO: 85497) (SEQ ID NO: 85498) hCV3084793 C/TCCCGGCTGGGCGCGGACATGGAG CCCGGCTGGGCGCGGACATGGAGG CAGCTTGCGCAGGTG GACGTTCACGTTT (SEQ ID NO: 85501) (SEQ ID NO: 85499) (SEQ ID NO: 85500)hCV3112686 C/G ACTTTGCTTCCCGAAGATAC ACTTTGCTTCCCGAAGATAGTCACCGCTCCACAGACTT (SEQ ID NO: 85502) (SEQ ID NO: 85503)(SEQ ID NO: 85504) hCV3135085 G/T CTGGAAATGGTTATGGGCTACTGGAAATGGTTATGGGA TTTATAGGCGTGAAACTAATTCTC (SEQ ID NO: 85505)(SEQ ID NO: 85506) (SEQ ID NO: 85507) hCV3187716 A/CCCTTCAATTCTGAAAAGTAGC CCTTCAATTCTGAAAAGTAG TTTGAGGTTGAGTGACATGTTC TAATCTAAG (SEQ ID NO: 85510) (SEQ ID NO: 85508) (SEQ ID NO: 85509)hCV3210838 C/T CTGCATTATTTCTATGACGC TTCTGCATTATTTCTATGACGTCAAAAAATGCCAACAGTTTAGA (SEQ ID NO: 85511) (SEQ ID NO: 85512)(SEQ ID NO: 85513) hCV3212009 A/G GTTCTCCCCTTTCAGTGTCTTCTCCCCTTTCAGTGTCC TGTCGGTGACTGTTCTGTTAA (SEQ ID NO: 85514)(SEQ ID NO: 85515) (SEQ ID NO: 85516) hCV3215409 A/GGTGGCTCATTACCAATCTCTT GTGGCTCATTACCAATCTCTC GGGCTCCATCAACATCAC(SEQ ID NO: 85517) (SEQ ID NO: 85518) (SEQ ID NO: 85519) hCV3223182 C/TTCGCAACTCACATCACTG GTCGCAACTCACATCACTA AGTTCTTGGAGGCATCTCAT(SEQ ID NO: 85520) (SEQ ID NO: 85521) (SEQ ID NO: 85522) hCV3275199 A/GCCATGCAACCAAACCAT CCATGCAACCAAACCAC CCTCTCATCCCTCTCATCTTT(SEQ ID NO: 85523) (SEQ ID NO: 85524) (SEQ ID NO: 85525) hCV334226 A/GGAGCCTGGGCCAAAT GAGCCTGGGCCAAAC CCTAAGAGGCTGGAAAGATAGAG(SEQ ID NO: 85526) (SEQ ID NO: 85527) (SEQ ID NO: 85528) hCV517658 T/CAATGGCCTTGGACTTGAT AATGGCCTTGGACTTGAC CTCTGCCATGCAAAACAC(SEQ ID NO: 85529) (SEQ ID NO: 85530) (SEQ ID NO: 85531) hCV529706 C/GGCGAGGACGAAGGGG GCGAGGACGAAGGGC GGAGGATGAATGGACAGACAA (SEQ ID NO: 85532)(SEQ ID NO: 85533) (SEQ ID NO: 85534) hCV529710 C/G CCGACCCGAACTAAAGGCCGACCCGAACTAAAGC CGCGTTCCCCATGTC (SEQ ID NO: 85535) (SEQ ID NO: 85536)(SEQ ID NO: 85537) hCV549926 C/T ACCATGGTCACCCTGG CACCATGGTCACCCTGAGGACTGAAAGCAATGTGAGAG (SEQ ID NO: 85538) (SEQ ID NO: 85539)(SEQ ID NO: 85540) hCV5687 A/G GCCCTCAGTGTGACTGAGAT GCCCTCAGTGTGACTGAGACCCAGGCATTTCCCATACAG (SEQ ID NO: 85541) (SEQ ID NO: 85542)(SEQ ID NO: 85543) hCV57888 A/G GCATAAAGCCAAGGTAGAAAGCATAAAGCCAAGGTAGAAG CCACTGGAACACTCACACAT (SEQ ID NO: 85544)(SEQ ID NO: 85545) (SEQ ID NO: 85546) hCV600632 A/C CGTCAATGCCCTCATCTGTCAATGCCCTCATCG GAGACTGCGATGTCTGAATAGT (SEQ ID NO: 85547)(SEQ ID NO: 85548) (SEQ ID NO: 85549) hCV7429784 A/GGGGTCATGGTACTCAATGAA GGGTCATGGTACTCAATGAG TGTACAAAAATGTTGTCACATACAG(SEQ ID NO: 85550) (SEQ ID NO: 85551) (SEQ ID NO: 85552) hCV7443062 T/CGGAGCAGGATGGTGAT GGAGCAGGATGGTGAC GGAAATATCTCGTTCTTGTTCTCT(SEQ ID NO: 85553) (SEQ ID NO: 85554) (SEQ ID NO: 85555) hCV7449808 A/GGGCTTACCTGGCCCAGT GCTTACCTGGCCCAGC CCTTCAGCCTCCAACATGA(SEQ ID NO: 85556) (SEQ ID NO: 85557) (SEQ ID NO: 85558) hCV7481138 A/CCGGATCTCTCGCAA CGGATCTCTCGCAC TGGAGGAGGTGATTCA (SEQ ID NO: 85559)(SEQ ID NO: 85560) (SEQ ID NO: 85561) hCV7490135 C/TGCAGTCCTGAACAAAGTAGATG CGCAGTCCTGAACAAAGTAGATA CGTGCATGTTTTGAAAAATGTA(SEQ ID NO: 85562) (SEQ ID NO: 85563) (SEQ ID NO: 85564) hCV7492597 C/TTACCTGAGCCAGTTGCAC TACCTGAGCCAGTTGCAT GGCTTCAGCTGAAGAAAGAG(SEQ ID NO: 85565) (SEQ ID NO: 85566) (SEQ ID NO: 85567) hCV7492601 T/AAAGGAGGTCTGCCTAAGGA AAGGAGGTCTGCCTAAGGT TACCTGCCTTTAAAGAACATTACT(SEQ ID NO: 85568) (SEQ ID NO: 85569) (SEQ ID NO: 85570) hCV7494810 C/GCCCGAGCGGACAGTG CCCGAGCGGACAGTC CAACTGCTGGCAGAATCTTC (SEQ ID NO: 85571)(SEQ ID NO: 85572) (SEQ ID NO: 85573) hCV7499900 T/CCACACCAGCAATGATGAAACT CACCAGCAATGATGAAACC GGCGGGTTCCAGACAA(SEQ ID NO: 85574) (SEQ ID NO: 85575) (SEQ ID NO: 85576) hCV7509650 C/TGCTCAGGACTATCTGCAGTG GGCTCAGGACTATCTGCAGTA TCCAAGCATGACTTCAGATTC(SEQ ID NO: 85577) (SEQ ID NO: 85578) (SEQ ID NO: 85579) hCV7514692 A/CGCCCCAACACCAGAGAA GCCCCAACACCAGAGAC CCACCACCACTCACCAGA(SEQ ID NO: 85580) (SEQ ID NO: 85581) (SEQ ID NO: 85582) hCV7514879 A/GGGCTGAACCCCGTCCT GCTGAACCCCGTCCC CTTTTTCCTGCATCCTGTCT (SEQ ID NO: 85583)(SEQ ID NO: 85584) (SEQ ID NO: 85585) hCV7580070 C/T TCCCATGCTTAAGGAAATGGATCCCATGCTTAAGGAAATA TGAGTGTACAATTCTAATTCTC (SEQ ID NO: 85586)(SEQ ID NO: 85587) AGACT (SEQ ID NO: 85588) hCV7582933 C/TCCAAAGGGTGTCAAGGC TCCAAAGGGTGTCAAGGT GCTGCTGGAATATGTTTGAGA(SEQ ID NO: 85589) (SEQ ID NO: 85590) (SEQ ID NO: 85591) hCV761961 C/TCACAGTCAAAGAATCAAGCG TCACAGTCAAAGAATCAAGCA AAATTCTTACCCTGAGTTCAGTTC(SEQ ID NO: 85592) (SEQ ID NO: 85593) (SEQ ID NO: 85594) hCV7686234 C/TGAGCGCTCTTTCTTGAC GAGCGCTCTTTCTTGAT GCGGAGGCCCTCTGTA (SEQ ID NO: 85595)(SEQ ID NO: 85596) (SEQ ID NO: 85597) hCV7798230 G/C GAGCGAGGGCTCAGGGAGCGAGGGCTCAGC CCTCCCTGGAGAATACTGTG (SEQ ID NO: 85598)(SEQ ID NO: 85599) (SEQ ID NO: 85600) hCV783184 G/T TGCGAGTCAAATCTCAAGACTGCGAGTCAAATCTCAAGAA CCTATTCCCGGCACTTCT (SEQ ID NO: 85601)(SEQ ID NO: 85602) (SEQ ID NO: 85603) hCV7841642 A/G ACCAGCTCCAGGGTGTTACCAGCTCCAGGGTGTC TGAAGTTTTGGAATGAGACTGAT (SEQ ID NO: 85604)(SEQ ID NO: 85605) (SEQ ID NO: 85606) hCV7900503 C/TCGTCTCCAGGAAAATCATAAC CGTCTCCAGGAAAATCATAAT TGAGTTATTGCTACTTCAGAATCAT(SEQ ID NO: 85607) (SEQ ID NO: 85608) (SEQ ID NO: 85609) hCV791476 C/TCAGAAAGTTCATGGTTTCG GCAGAAAGTTCATGGTTTCA CCGGGGAGGAAGAGTAG(SEQ ID NO: 85610) (SEQ ID NO: 85611) (SEQ ID NO: 85612) hCV795442 A/GCCATTCAATGCAATACGTCA CATTCAATGCAATACGTCG CCTCTCCTTCCAGAACCAGT(SEQ ID NO: 85613) (SEQ ID NO: 85614) (SEQ ID NO: 85615) hCV8022252 A/GCACTGGTCTCAGATGTGATGT ACTGGTCTCAGATGTGATGC GGGCTGGCAGGGTATAG(SEQ ID NO: 85616) (SEQ ID NO: 85617) (SEQ ID NO: 85618) hCV8339791 C/TTTCTACAACGTGGACATGG ACTTCTACAACGTGGACATGA GCCTGCCACTCACATTACA(SEQ ID NO: 85619) (SEQ ID NO: 85620) (SEQ ID NO: 85621) hCV8400671 A/GTTGTTAACATATACTTACTGGAGA TGTTAACATATACTTACTGGAGG TGCCTCTTCTTTATTTATGTC(SEQ ID NO: 85622) (SEQ ID NO: 85623) (SEQ ID NO: 85624) hCV8705506 C/GCCACTTCGGGTTCCTC CCACTTCGGGTTCCTG CCCTGGCTTCAACATGA (SEQ ID NO: 85625)(SEQ ID NO: 85626) (SEQ ID NO: 85627) hCV8708473 A/G GCAACAGGACACCTGAAGCAACAGGACACCTGAG GAGTGACAGGAGGCTGCTTA (SEQ ID NO: 85628)(SEQ ID NO: 85629) (SEQ ID NO: 85630) hCV8718197 A/G CCTCTGAGGCCTGAGAAACCTCTGAGGCCTGAGAAG GTCCTGATTCCTCATTTCTTTC (SEQ ID NO: 85631)(SEQ ID NO: 85632) (SEQ ID NO: 85633) hCV8722981 C/T GCGCTGGTTTGGAGGGCGCTGGTTTGGAGA TGGCACAGGCAGTATTAAGTAG (SEQ ID NO: 85634)(SEQ ID NO: 85635) (SEQ ID NO: 85636) hCV8726331 A/G TGGTCTGTTCCCTGGACAGGTCTGTTCCCTGGACG TGCGGTCACACTGACTGAG (SEQ ID NO: 85637)(SEQ ID NO: 85638) (SEQ ID NO: 85639) hCV8726337 A/G CACATTCACGGTCACCTTCACATTCACGGTCACCTC CATTGCCCGAGCTCAA (SEQ ID NO: 85640)(SEQ ID NO: 85641) (SEQ ID NO: 85642) hCV8737990 C/T GTCCTTGCAAGTATCCGGGTCCTTGCAAGTATCCA GCACTACAGCTGAGTCCTTTTC (SEQ ID NO: 85643)(SEQ ID NO: 85644) (SEQ ID NO: 85645) hCV8815434 G/T GGTGGTCCCTTTGGACGGTGGTCCCTTTGT CCTCGCAGGCCTTCTC (SEQ ID NO: 85646) (SEQ ID NO: 85647)(SEQ ID NO: 85648) hCV8827241 C/G TCAAGAGGACAGTGATGGTGTCAAGAGGACAGTGATGGTC TGGTTAGAATCTGTGAAGGAACTA (SEQ ID NO: 85649)(SEQ ID NO: 85650) (SEQ ID NO: 85651) hCV8849004 A/GAGAGAGTGCACAGTAGATGT GAGAGTGCACAGTAGATGC AAACCTGAGTTTTAACTTGGTGA(SEQ ID NO: 85652) (SEQ ID NO: 85653) (SEQ ID NO: 85654) hCV8851080 A/GGGCACTGCCCGCTT GGCACTGCCCGCTC CGCTTCCTGGAGAGATACATC (SEQ ID NO: 85655)(SEQ ID NO: 85656) (SEQ ID NO: 85657) hCV8851084 A/G CAGTGCCGGACAGGACAGTGCCGGACAGGG CCGCCCGGCACTAAG (SEQ ID NO: 85658) (SEQ ID NO: 85659)(SEQ ID NO: 85660) hCV8851085 A/G GCTCGTAGTTGTGTCTGCATGCTCGTAGTTGTGTCTGCAC CGCTTCCTGGAGAGATACAT (SEQ ID NO: 85661)(SEQ ID NO: 85662) (SEQ ID NO: 85663) hCV8895373 A/G AGGACTTCCGTGTCTTAGGACTTCCGTGTCTC ACAGATGCCAGCAATACAGA (SEQ ID NO: 85664)(SEQ ID NO: 85665) (SEQ ID NO: 85666) hCV8907537 C/G GCCTATCCATCCTGCCGCCTATCCATCCTGCG GGTAGGAGAGCACTGAGAATACT (SEQ ID NO: 85667)(SEQ ID NO: 85668) (SEQ ID NO: 85669) hCV8921137 A/T CAGAGCCTGCACATCAATCAGAGCCTGCACATCAAA GGCAAGGTCTCTGATCTGTAA (SEQ ID NO: 85670)(SEQ ID NO: 85671) (SEQ ID NO: 85672) hCV8921288 C/A CCGCAGAGGTGTGGGCCGCAGAGGTGTGGT CATTTTGCGGTGGAAATG (SEQ ID NO: 85673) (SEQ ID NO: 85674)(SEQ ID NO: 85675) hCV8931357 A/G TTATTGACACTTTCCAGTAAATTATTGACACTTTCCAGTAAA AGGCACAAGCTGCAGATAA TAATT TAATC (SEQ ID NO: 85678)(SEQ ID NO: 85676) (SEQ ID NO: 85677) hCV8952817 C/GCGCATCCAGAACATTCTATG CGCATCCAGAACATTCTATC GCAGCTTCCCATCATACACT(SEQ ID NO: 85679) (SEQ ID NO: 85680) (SEQ ID NO: 85681) hCV905013 G/TACACCTCGCCCAGTAATC GACACCTCGCCCAGTAATA CCCCCTCTCCAGATTACATT(SEQ ID NO: 85682) (SEQ ID NO: 85683) (SEQ ID NO: 85684) hCV9077561 G/AAGAAGGTGGGATCCAAAC AGAAGGTGGGATCCAAAT AGAAACCATCATGCTGAGGT(SEQ ID NO: 85685) (SEQ ID NO: 85686) (SEQ ID NO: 85687) hCV9485713 T/CGCCCAGAGACAGGAAAAT GCCCAGAGACAGGAAAAC GCCTGCCCTCTGTTCA(SEQ ID NO: 85688) (SEQ ID NO: 85689) (SEQ ID NO: 85690) hCV9506149 A/TCTGCTGGCCGTCCT TGCTGGCCGTCCA ACTCACGCTTGCTTTGACT (SEQ ID NO: 85691)(SEQ ID NO: 85692) (SEQ ID NO: 85693) hCV9546471 A/CCTCAGGAAGCTAAAAGGTGA TCAGGAAGCTAAAAGGTGC CCTAATATCCCCTCCAGAACTAT(SEQ ID NO: 85694) (SEQ ID NO: 85695) (SEQ ID NO: 85696) hCV9546517 G/AACATTTCAGAACCTATCTTCTTC ACATTTCAGAACCTATCTTCTTT AGTTCATATGGACCAGACATCA(SEQ ID NO: 85697) (SEQ ID NO: 85698) (SEQ ID NO: 85699) hCV9698595 A/TGCTGGTCATCCTCATCCA TGCTGGTCATCCTCATCCT ACCGTCCTGGCTTTTAAAG(SEQ ID NO: 85700) (SEQ ID NO: 85701) (SEQ ID NO: 85702)

TABLE 6 Placebo Significant Associations Between SNP Overall* SNPEffect** Patients Odds Ratio (95% CI) Signifi- Genotypes and QualitativePhenotypes Ch Square Test Ch Square Test n/total (%) 2 Rare Alleles vs.1 Rare Allele vs. cance Public Marker Stratum Phenotype statisticp-value statistic p-value 0 Rare Alleles 1 Rare Alleles 2 Rare Alleles 0Rare Alleles 0 Rare Alleles level ACACB hCV- All Fatal Coronary 7.53390.0231 6.6562 0.0099 34/989 (3.4%) 17/432 (3.9%) 5/43 (11.6%) 1.15 (0.62to 2.05) 3.70 (1.22 to 9.23) p < 0.05 16166043 Patients Heart DiseaseACACB hCV- All Coronary 10.3188 0.0057 9.2668 0.0023 216/989 64/432(14.8%) 6/43 (14.0%) 0.62 (0.46 to 0.84) 0.58 (0.22 to 1.30) p <16166043 Patients Artery Bypass (21.8%) 0.005 or Revascularization ACACBhCV- All Hosp. for 13.3305 0.0013 9.466 0.0021 201/989 58/432 (13.4%)3/43 (7.0%) 0.61 (0.44 to 0.83) 0.29 (0.07 to 0.82) p < 16166043Patients Unstable Angina (20.3%) 0.005 ACACB hCV- All Family History8.0471 0.0179 6.7129 0.0096 430/989 156/432 14/43 (32.6%) 0.74 (0.58 to0.93) 0.63 (0.32 to 1.18) p < 0.05 16166043 Patients of CV Disease(43.5%) (36.1%) ACE hCV- All Fatal Coronary 14.0826 0.0009 5.2478 0.02254/1454 (3.7%) 2/18 (11.1%) 1/2 (50.0%) 3.24 (0.51 to 11.78) 25.93 (1.02to p < 0.05 11942529 Patients Heart Disease 660.87) ACE hCV- AllCardiovascular 12.0994 0.0024 4.8517 0.0276 61/1454 (4.2%) 2/18 (11.1%)1/2 (50.0%) 2.86 (0.45 to 10.34) 22.84 (0.90 to p < 0.05 11942529Patients Mortality 581.53) ACE hCV- All Fatal 12.0994 0.0024 4.85170.0276 61/1454 (4.2%) 2/18 (11.1%) 1/2 (50.0%) 2.86 (0.45 to 10.34)22.84 (0.90 to p < 0.05 11942529 Patients Atherosclerotic Cardiovascular581.53) Disease ADA- hCV- All Fatal CHD/Definite 7.3723 0.0251 6.57650.0103 92/872 (10.6%) 78/511 (15.3%) 14/90 (15.6%) 1.53 (1.10 to 2.11)1.56 (0.82 to 2.79) p < 0.05 MTS1 529706 Patients Non-fatal MI ADA- hCV-All Fatal Coronary 7.4845 0.0237 7.1633 0.0074 24/872 (2.8%) 29/511(5.7%) 4/90 (4.4%) 2.13 (1.23 to 3.72) 1.64 (0.48 to 4.38) p < 0.05 MTS1529706 Patients Heart Disease ADA- hCV- All Total Mortality 12.47050.002 12.0029 0.0005 40/872 (4.6%) 48/511 (9.4%) 6/90 (6.7%) 2.16 (1.40to 3.34) 1.49 (0.55 to 3.36) p < MTS1 529706 Patients 0.005 ADA- hCV-All Cardiovascular 10.455 0.0054 9.947 0.0016 26/872 (3.0%) 34/511(6.7%) 4/90 (4.4%) 2.32 (1.38 to 3.94) 1.51 (0.44 to 4.00) p < MTS1529706 Patients Mortality 0.005 ADA- hCV- All Fatal 10.455 0.0054 9.9470.0016 26/872 (3.0%) 34/511 (6.7%) 4/90 (4.4%) 2.32 (1.38 to 3.94) 1.51(0.44 to 4.00) p < MTS1 529706 Patients Atherosclerotic Cardiovascular0.005 Disease ANXA9 hCV- All Hosp. for 8.1528 0.017 4.6114 0.0318179/1089 75/353 (21.2%) 10/32 (31.3%) 1.37 (1.01 to 1.85) 2.31 (1.03 to4.84) p < 0.05 8022252 Patients Unstable Angina (16.4%) ANXA9 hCV- AllCARE MI: 10.3373 0.0057 9.0759 0.0026 93/1089 (8.5%) 31/352 (8.8%) 8/32(25.0%) 1.03 (0.67 to 1.57) 3.57 (1.47 to 7.85) p < 8022252 Patients NonQ-Wave MI 0.005 APOA4 hCV- All Fatal/Non-fatal 7.0664 0.0292 6.169 0.01372/1106 (6.5%) 23/347 (6.6%) 5/25 (20.0%) 1.02 (0.62 to 1.63) 3.59 (1.17to 9.17) p < 0.05 11482766 Patients Cerebrovascular Disease APOA4 hCV-All Any Report 9.6951 0.0078 7.46 0.0063 43/1106 (3.9%) 12/347 (3.5%)4/25 (16.0%) 0.89 (0.44 to 1.65) 4.71 (1.33 to 13.04) p < 0.05 11482766Patients of Stroke During CARE APOA4 hCV- All 1st Stroke Occurred11.7036 0.0029 9.2108 0.0024 36/1106 (3.3%) 12/347 (3.5%) 4/25 (16.0%)1.07 (0.53 to 2.01) 5.66 (1.59 to 15.83) p < 11482766 Patients DuringCARE 0.005 APOC3 hCV- All Fatal/Non-fatal 13.3844 0.0012 9.6921 0.001975/1211 (6.2%) 21/255 (8.2%) 4/13 (30.8%) 1.36 (0.80 to 2.21) 6.73 (1.79to 21.19) p < 8907537 Patients Cerebrovascular 0.005 Disease APOC3 hCV-All Fatal/Non-fatal 7.2676 0.0264 4.0221 0.0449 486/1211 89/255 (34.9%)9/13 (69.2%) 0.80 (0.60 to 1.06) 3.36 (1.09 to 12.44) p < 0.05 8907537Patients Atherosclerotic (40.1%) CV Disease APOC3 hCV- All History of6.1599 0.046 5.9094 0.0151 375/1211 99/255 (38.8%) 5/13 (38.5%) 1.42(1.07 to 1.87) 1.39 (0.42 to 4.20) p < 0.05 8907537 PatientsPercutaneous (31.0%) Transluminal Coronary Angioplasty APOC3 hCV- AllAny Report of 6.6883 0.0353 5.5134 0.0189 71/1211 (5.9%) 16/255 (6.3%)3/13 (23.1%) 1.08 (0.59 to 1.83) 4.82 (1.06 to 16.16) p < 0.05 8907537Patients Stroke Prior to or During CARE APOC3 hCV- All Any Report12.4845 0.0019 9.0194 0.0027 46/1211 (3.8%) 10/255 (3.9%) 3/13 (23.1%)1.03 (0.49 to 1.99) 7.60 (1.66 to 25.83) p < 8907537 Patients of Stroke0.005 During CARE APOC3 hCV- All 1st Stroke Occurred 15.0987 0.000510.5154 0.0012 39/1211 (3.2%) 10/255 (3.9%) 3/13 (23.1%) 1.23 (0.57 to2.40) 9.02 (1.97 to 30.85) p < 8907537 Patients During CARE 0.005 APOEhCV- All Fatal/Non-fatal 6.5129 0.0385 5.792 0.0161 70/1074 (6.5%)24/368 (6.5%) 6/34 (17.6%) 1.00 (0.61 to 1.59) 3.07 (1.12 to 7.20) p <0.05 3084793 Patients Cerebrovascular Disease CASP1 hCV- All FatalCHD/Definite 11.6894 0.0006 11.4335 0.0007 132/1187 53/285 (18.6%) 0/0(0.0%) 1.83 (1.28 to 2.58) p < 16276495 Patients Non-fatal MI (11.1%)0.005 CASP1 hCV- All Fatal Coronary 7.4141 0.0065 7.0957 0.0077 38/1187(3.2%) 19/285 (6.7%) 0/0 (0.0%) 2.16 (1.20 to 3.76) p < 0.05 16276495Patients Heart Disease CASP1 hCV- All Non-fatal MI 7.3586 0.0067 7.24960.0071 134/1187 49/285 (17.2%) 0/0 (0.0%) 1.63 (1.13 to 2.32) p < 0.0516276495 Patients (def & prob) (11.3%) CASP1 hCV- All Fatal/Non-fatal10.8754 0.001 10.672 0.0011 148/1187 57/285 (20.0%) 0/0 (0.0%) 1.76(1.25 to 2.45) p < 16276495 Patients MI (def & prob) (12.5%) 0.005 CASP1hCV- All Cardiovascular 6.0571 0.0139 5.858 0.0155 44/1187 (3.7%) 20/285(7.0%) 00 (0.0%) 1.96 (1.12 to 3.34) p < 0.05 16276495 PatientsMortality CASP1 hCV- All Fatal Atherosclerotic 6.0571 0.0139 5.8580.0155 44/1187 (3.7%) 20/285 (7.0%) 0/0 (0.0%) 1.96 (1.12 to 3.34) p <0.05 16276495 Patients Cardiovascular Disease CCR5 hCV- All FatalCHD/Definite 9.0507 0.0108 4.5709 0.0325 177/1398 5/61 (8.2%) 2/3(66.7%) 0.62 (0.21 to 1.42) 13.79 (1.32 to p < 0.05 9698595 PatientsNon-fatal MI (12.7%) 297.56) CCR5 hCV- All Fatal Coronary 7.7729 0.02054.1219 0.0423 55/1398 (3.9%) 1/61 (1.6%) 1/3 (33.3%) 0.41 (0.02 to 1.90)12.21 (0.56 to p < 0.05 9698595 Patients Heart Disease 129.27) CCR5 hCV-All Fatal/Non-fatal 7.255 0.0266 4.1925 0.0406 195/1398 7/61 (11.5%) 2/3(66.7%) 0.80 (0.33 to 1.67) 12.34 (1.18 to p < 0.05 9698595 Patients MI(def & prob) (13.9%) 266.05) CCR5 hCV- All More Than 7.4573 0.024 3.99660.0456 205/1398 12/61 (19.7%) 2/3 (66.7%) 1.43 (0.71 to 2.64) 11.62(1.11 to p < 0.05 9698595 Patients 1 Prior MI (14.7%) 250.94) CCRL2 hCV-All Fatal CHD/Definite 9.2116 0.01 6.3488 0.0117 151/1278 29/184 (15.8%)5/14 (35.7%) 1.40 (0.89 to 2.12) 4.15 (1.26 to 12.17) p < 0.05 25637308Patients Non-fatal MI (11.8%) CCRL2 hCV- All Fatal CHD/Definite 8.52180.0141 7.8587 0.0051 75/531 (14.1%) 92/689 (13.4%) 17/244 (7.0%) 0.94(0.68 to 1.30) 0.46 (0.26 to 0.77) p < 0.05 25637309 Patients Non-fatalMI CCRL2 hCV- All Fatal/Non-fatal 7.0061 0.0301 5.4247 0.0199 78/531(14.7%) 105/689 (15.2%) 21/244 (8.6%) 1.04 (0.76 to 1.44) 0.55 (0.32 to0.89) p < 0.05 25637309 Patients MI (def & prob) CD44 hCV- AllFatal/Non-fatal 6.5508 0.0105 5.9272 0.0149 94/1446 (6.5%) 6/34 (17.6%)0/0 (0.0%) 3.08 (1.13 to 7.15) p < 0.05 25593221 PatientsCerebrovascular Disease CD44 hCV- All Any report of 4.5325 0.0333 4.17510.041 85/1446 (5.9%) 5/34 (14.7%) 0/0 (0.0%) 2.76 (0.92 to 6.74) p <0.05 25593221 Patients Stroke Prior to or During CARE CD44 hCV- All Anyreport of Stroke 5.5006 0.019 4.8895 0.027 55/1446 (3.8%) 4/34 (11.8%)0/0 (0.0%) 3.37 (0.98 to 8.92) p < 0.05 25593221 Patients During CARECD44 hCV- All 1st Stroke Occurred 6.9887 0.0082 6.0383 0.014 48/1446(3.3%) 4/34 (11.8%) 0/0 (0.0%) 3.88 (1.12 to 10.33) p < 0.05 25593221Patients During CARE CHUK hCV- All Hosp. for 12.3061 0.0021 11.5830.0007 51/407 (12.5%) 136/724 (18.8%) 73/331 (22.1%) 1.62 (1.15 to 2.30)1.98 (1.34 to 2.94) p < 1345898 Patients Unstable Angina 0.005 CHUK hCV-All History of Coronary 6.4389 0.04 5.8619 0.0155 126/407 176/724(24.3%) 82/331 (24.8%) 0.72 (0.55 to 0.94) 0.73 (0.53 to 1.02) p < 0.051345898 Patients Artery (31.0%) Bypass Graft CHUK hCV- All FamilyHistory 6.7236 0.0347 6.0525 0.0139 179/407 305/724 (42.1%) 116/331(35.0%) 0.93 (0.73 to 1.19) 0.69 (0.51 to 0.93) p < 0.05 1345898Patients of CV Disease (44.0%) COL6A2 hCV- All Non-fatal MI 7.65470.0218 6.8555 0.0088 54/372 (14.5%) 100/755 (13.2%) 29/352 (8.2%) 0.90(0.63 to 1.29) 0.53 (0.33 to 0.85) p < 0.05 2811372 Patients (def &prob) COL6A2 hCV- All Fatal/Non-fatal 7.0498 0.0295 6.1008 0.0135 59/372(15.9%) 112/755 (14.8%) 34/352 (9.7%) 0.92 (0.66 to 1.31) 0.57 (0.36 to0.88) p < 0.05 2811372 Patients MI (def & prob) COL6A2 hCV- All CARE MI:Non 6.441 0.0399 5.9297 0.0149 40/372 (10.8%) 72/754 (9.5%) 20/352(5.7%) 0.88 (0.59 to 1.33) 0.50 (0.28 to 0.86) p < 0.05 2811372 PatientsQ-Wave MI CTSB hCV- All Fatal Coronary 7.8799 0.0194 6.4458 0.011141/1107 (3.7%) 12/340 (3.5%) 4/29 (13.8%) 0.95 (0.47 to 1.78) 4.16 (1.19to 11.34) p < 0.05 8339791 Patients Heart Disease CTSB hCV- AllCardiovascular 11.9462 0.0025 9.3211 0.0023 46/1107 (4.2%) 13/340 (3.8%)5/29 (17.2%) 0.92 (0.47 to 1.67) 4.81 (1.56 to 12.23) p < 8339791Patients Mortality 0.005 CTSB hCV- All Fatal 11.9462 0.0025 9.32110.0023 46/1107 (4.2%) 13/340 (3.8%) 5/29 (17.2%) 0.92 (0.47 to 1.67)4.81 (1.56 to 12.23) p < 8339791 Patients Atherosclerotic 0.005Cardiovascular Disease CUBN hCV- All Congestive 6.8723 0.0322 6.48070.0109 38/636 (6.0%) 52/629 (8.3%) 22/191 (11.5%) 1.42 (0.92 to 2.20)2.05 (1.16 to 3.53) p < 0.05 3135085 Patients Heart Failure CUBN hCV-All History of Diabetes 11.8699 0.0026 11.0773 0.0009 75/636 (11.8%)100/629 (15.9%) 41/191 (21.5%) 1.41 (1.03 to 1.96) 2.05 (1.33 to 3.10) p< 3135085 Patients 0.005 CUBN hCV- All Insulin 11.1304 0.0038 10.03310.0015 9/636 (1.4%) 19/629 (3.0%) 11/191 (5.8%) 2.17 (1.00 to 5.07) 4.26(1.74 to 10.71) p < 3135085 Patients 0.005 CX3CR1 hCV5687 All Hosp. for15.5209 0.0004 13.3955 0.0003 458/1000 200/427 (46.8%) 31/40 (77.5%)1.04 (0.83 to 1.31) 4.08 (2.00 to 9.18) p < Patients Cardiovascular(45.8%) 0.0005 Disease CX3CR1 hCV5687 All Hosp. for 10.6459 0.00498.7005 0.0032 164/1000 85/427 (19.9%) 14/40 (35.0%) 1.27 (0.95 to 1.69)2.75 (1.37 to 5.29) p < Patients Unstable Angina (16.4%) 0.005 CX3CR1hCV5687 All Total Cardiovascular 14.0718 0.0009 12.272 0.0005 473/1000205/427 (48.0%) 31/40 (77.5%) 1.03 (0.82 to 1.29) 3.84 (1.88 to 8.64) p< Patients Disease Events (47.3%) 0.005 CX3CR1 hCV5687 AllFatal/Non-fatal 7.2089 0.0272 6.7757 0.0092 389/1000 167/427 (39.1%)24/40 (60.0%) 1.01 (0.80 to 1.27) 2.36 (1.25 to 4.57) p < 0.05 PatientsAtherosclerotic (38.9%) CV Disease CX3CR1 hCV5687 All CARE MI: 8.83350.0121 5.299 0.0213 614/1000 286/427 (67.0%) 32/40 (80.0%) 1.28 (1.01 to1.62) 2.52 (1.20 to 5.91) p < 0.05 Patients Q-Wave MI (61.4%) CX3CR1hCV- All Fatal CHD/Definite 9.487 0.0087 8.1574 0.0043 110/756 57/606(9.4%) 17/105 (16.2%) 0.61 (0.43 to 0.85) 1.14 (0.63 to 1.94) p <7900503 Patients Non-fatal MI (14.6%) 0.005 CX3CR1 hCV- All Non-fatal MI11.6633 0.0029 7.2394 0.0071 106/756 56/606 (9.2%) 20/105 (19.0%) 0.62(0.44 to 0.88) 1.44 (0.83 to 2.41) p < 0.05 7900503 Patients (def &prob) (14.0%) CX3CR1 hCV- All Fatal/Non-fatal 14.5731 0.0007 8.74010.0031 119/756 62/606 (10.2%) 23/105 (21.9%) 0.61 (0.44 to 0.84) 1.50(0.89 to 2.45) p < 7900503 Patients MI (def & prob) (15.7%) 0.005 CX3CR1hCV- All Coronary 6.8382 0.0327 4.3331 0.0374 149/756 107/606 (17.7%)30/105 (28.6%) 0.87 (0.66 to 1.15) 1.63 (1.02 to 2.56) p < 0.05 7900503Patients Artery Bypass (19.7%) or Revascularization CX3CR1 hCV- AllHosp. for 12.0615 0.0024 9.2554 0.0023 354/756 270/606 (44.6%) 66/105(62.9%) 0.91 (0.74 to 1.13) 1.92 (1.27 to 2.95) p < 7900503 PatientsCardiovascular (46.8%) 0.005 Disease CX3CR1 hCV- All Hosp. for 7.70140.0213 7.5098 0.0061 125/756 109/606 (18.0%) 29/105 (27.6%) 1.11 (0.83to 1.47) 1.93 (1.19 to 3.05) p < 0.05 7900503 Patients Unstable Angina(16.5%) CX3CR1 hCV- All Total Coronary Heart 11.1872 0.0037 6.83720.0089 267/756 193/606 (31.8%) 51/105 (48.6%) 0.86 (0.68 to 1.07) 1.73(1.15 to 2.61) p < 0.05 7900503 Patients Disease Events (35.3%) CX3CR1hCV- All Total Cardiovascular 11.9681 0.0025 8.402 0.0037 367/756276/606 (45.5%) 67/105 (63.8%) 0.89 (0.72 to 1.10) 1.87 (1.23 to 2.87) p< 7900503 Patients Disease Events (48.5%) 0.005 CX3CR1 hCV- AllFatal/Non-fatal 11.1546 0.0038 6.4222 0.0113 304/756 220/606 (36.3%)56/105 (53.3%) 0.85 (0.68 to 1.06) 1.70 (1.13 to 2.57) p < 0.05 7900503Patients Atherosclerotic (40.2%) CV Disease DBH hCV- All FatalCHD/Definite 6.3707 0.0414 4.6865 0.0304 160/1261 21/198 (10.6%) 4/11(36.4%) 0.82 (0.49 to 1.29) 3.93 (1.02 to 13.17) p < 0.05 12020339Patients Non-fatal MI (12.7%) DBH hCV- All Fatal Coronary 6.4202 0.04044.5927 0.0321 49/1261 (3.9%) 6/198 (3.0%) 2/11 (18.2%) 0.77 (0.29 to1.69) 5.50 (0.82 to 22.04) p < 0.05 12020339 Patients Heart Disease ELNhCV- All Fatal CHD/Definite 7.0192 0.0299 5.8657 0.0154 77/507 (15.2%)84/721 (11.7%) 21/241 (8.7%) 0.74 (0.53 to 1.03) 0.53 (0.31 to 0.87) p <0.05 1253630 Patients Non-fatal MI ELN hCV- All Non-fatal MI 6.45090.0397 6.2416 0.0125 73/507 (14.4%) 88/721 (12.2%) 19/241 (7.9%) 0.83(0.59 to 1.16) 0.51 (0.29 to 0.85) p < 0.05 1253630 Patients (def &prob) F8 hCV- All CARE MI: Non 11.1257 0.0038 7.548 0.006 109/120019/263 (7.2%) 4/11 (36.4%) 0.78 (0.46 to 1.26) 5.72 (1.48 to 19.25) p <0.05 11359098 Patients Q-Wave MI (9.1%) FGB hCV- All Cardiovascular6.2697 0.0435 5.2663 0.0217 35/1006 (3.5%) 26/418 (6.2%) 3/40 (7.5%)1.84 (1.08 to 3.09) 2.25 (0.53 to 6.63) p < 0.05 7429784 PatientsMortality FGB hCV- All Fatal 6.2697 0.0435 5.2663 0.0217 35/1006 (3.5%)26/418 (6.2%) 3/40 (7.5%) 1.84 (1.08 to 3.09) 2.25 (0.53 to 6.63) p <0.05 7429784 Patients Atherosclerotic Cardiovascular Disease HDLBP hCV-All Hosp. for 6.3052 0.0427 5.2308 0.0222 157/802 91/545 (16.7%) 12/114(10.5%) 0.82 (0.62 to 1.09) 0.48 (0.25 to 0.87) p < 0.05 22274624Patients Unstable Angina (19.6%) HFE hCV- All History of 6.147 0.04635.3105 0.0212 199/1086 85/355 (23.9%) 10/39 (25.6%) 1.40 (1.05 to 1.87)1.54 (0.70 to 3.10) p < 0.05 1085600 Patients Angina Pectoris (18.3%)HFE hCV- All History of Diabetes 11.6431 0.003 6.3752 0.0116 166/108640/355 (11.3%) 12/39 (30.8%) 0.70 (0.48 to 1.01) 2.46 (1.18 to 4.85) p <0.05 1085600 Patients (15.3%) HLA- hCV- All Total Mortality 6.67930.0354 6.1772 0.0129 57/994 (5.7%) 29/429 (6.8%) 8/56 (14.3%) 1.19 (0.74to 1.88) 2.74 (1.16 to 5.78) p < 0.05 DPA1 15760070 Patients HLA- hCV-All Coronary 9.3862 0.0092 7.003 0.0081 200/994 86/429 (20.0%) 2/56(3.6%) 1.00 (0.75 to 1.32) 0.15 (0.02 to 0.48) p < 0.05 DPA1 15760070Patients Artery Bypass (20.1%) or Revascularization HLA- hCV- AllHistory of 8.325 0.0156 7.753 0.0054 315/994 135/429 (31.5%) 28/56(50.0%) 0.99 (0.78 to 1.26) 2.16 (1.25 to 3.71) p < 0.05 DPA1 15760070Patients Percutaneous (31.7%) Transluminal Coronary Angioplasty HLA-hCV- All Non-fatal 7.4596 0.024 6.8238 0.009 98/708 (13.8%) 78/632(12.3%) 7/132 (5.3%) 0.88 (0.64 to 1.20) 0.35 (0.14 to 0.72) p < 0.05DPB1 25651174 Patients MI (def & prob) HLA- hCV- All Coronary 9.75270.0076 6.5581 0.0104 137/708 137/632 (21.7%) 13/132 (9.8%) 1.15 (0.88 to1.51) 0.46 (0.24 to 0.80) p < 0.05 DPB1 25651174 Patients Artery Bypass(19.4%) or Revascularization HLA- hCV- All Hosp. for 10.6608 0.00487.5713 0.0059 334/708 314/632 (49.7%) 45/132 (34.1%) 1.11 (0.89 to 1.37)0.58 (0.39 to 0.85) p < 0.05 DPB1 25651174 Patients Cardiovascular(47.2%) Disease HLA- hCV- All Total Coronary 9.49 0.0087 9.0492 0.0026258/708 225/632 (35.6%) 30/132 (22.7%) 0.96 (0.77 to 1.21) 0.51 (0.33 to0.78) p < DPB1 25651174 Patients Heart Disease (36.4%) 0.005 Events HLA-hCV- All Total 7.7145 0.0211 6.0912 0.0136 346/708 318/632 (50.3%)49/132 (37.1%) 1.06 (0.86 to 1.31) 0.62 (0.42 to 0.90) p < 0.05 DPB125651174 Patients Cardiovascular (48.9%) Disease Events HLA- hCV- AllFatal/Non-fatal 9.2044 0.01 8.7506 0.0031 291/708 255/632 (40.3%) 36/132(27.3%) 0.97 (0.78 to 1.21) 0.54 (0.35 to 0.80) p < DPB1 25651174Patients Atherosclerotic (41.1%) 0.005 CV Disease HLA- hCV- All TotalCoronary 8.5603 0.0138 7.9839 0.0047 342/950 161/465 (34.6%) 11/62(17.7%) 0.94 (0.75 to 1.19) 0.38 (0.19 to 0.72) p < DPB1 8851084Patients Heart Disease (36.0%) 0.005 Events HLA- hCV- AllFatal/Non-fatal 7.3278 0.0256 6.5972 0.0102 390/950 178/465 (38.3%)15/62 (24.2%) 0.89 (0.71 to 1.12) 0.46 (0.25 to 0.81) p < 0.05 DPB18851084 Patients Atherosclerotic (41.1%) CV Disease HLA- hCV- AllCoronary 7.4082 0.0246 5.7094 0.0169 174/894 107/506 (21.1%) 6/76 (7.9%)1.11 (0.85 to 1.45) 0.36 (0.14 to 0.77) p < 0.05 DPB1 8851085 PatientsArtery Bypass (19.5%) or Revascularization HLA- hCV- All Hosp. for7.6098 0.0223 7.2388 0.0071 428/894 241/506 (47.6%) 24/76 (31.6%) 0.99(0.80 to 1.23) 0.50 (0.30 to 0.82) p < 0.05 DPB1 8851085 PatientsCardiovascular (47.9%) Disease HLA- hCV- All Total Coronary 8.09290.0175 7.7109 0.0055 321/894 177/506 (35.0%) 15/76 (19.7%) 0.96 (0.76 to1.21) 0.44 (0.24 to 0.76) p < 0.05 DPB1 8851085 Patients Heart Disease(35.9%) Events HLA- hCV- All Total 6.441 0.0399 6.2467 0.0124 441/894246/506 (48.6%) 26/76 (34.2%) 0.97 (0.78 to 1.21) 0.53 (0.32 to 0.87) p< 0.05 DPB1 8851085 Patients Cardiovascular (49.3%) Disease Events HLA-hCV- All Fatal/Non-fatal 8.9261 0.0115 8.4377 0.0037 367/894 197/506(38.9%) 18/76 (23.7%) 0.92 (0.73 to 1.14) 0.45 (0.25 to 0.75) p < DPB18851085 Patients Atherosclerotic (41.1%) 0.005 CV Disease HSPG2 hCV- AllHosp. for 7.3564 0.0253 5.9731 0.0145 217/1246 42/223 (18.8%) 5/10(50.0%) 1.10 (0.76 to 1.57) 4.74 (1.31 to p < 0.05 1603656 PatientsUnstable Angina (17.4%) 17.18) HSPG2 hCV- All History of 16.9406 0.000210.423 0.0012 248/1246 38/223 (17.0%) 7/10 (70.0%) 0.83 (0.56 to 1.19)9.39 (2.59 to p < 1603656 Patients Angina Pectoris (19.9%) 43.80) 0.005HSPG2 hCV- All Coronary 6.4646 0.0395 4.1122 0.0426 249/1313 36/159(22.6%) 3/5 (60.0%) 1.25 (0.83 to 1.84) 6.40 (1.06 to p < 0.05 1603697Patients Artery Bypass (19.0%) 48.85) or Revascularization HSPG2 hCV-All Hosp. for 8.9933 0.0111 4.6813 0.0305 225/1313 36/159 (22.6%) 3/5(60.0%) 1.42 (0.94 to 2.09) 7.25 (1.20 to p < 0.05 1603697 PatientsUnstable Angina (17.1%) 55.30) HSPG2 hCV- All History of 11.8532 0.00276.1384 0.0132 262/1313 28/159 (17.6%) 4/5 (80.0%) 0.86 (0.55 to 1.30)16.03 (2.36 to p < 0.05 1603697 Patients Angina Pectoris (20.0%) 314.38)HSPG2 hCV- All History of Stroke 6.362 0.0415 4.1405 0.0419 32/1313(2.4%) 5/159 (3.1%) 1/5 (20.0%) 1.30 (0.44 to 3.11) 10.01 (0.50 to p <0.05 1603697 Patients 70.04) IGF1R hCV- All Fatal CHD/Definite 12.01290.0025 8.8843 0.0029 169/1418 15/59 (25.4%) 1/2 (50.0%) 2.52 (1.33 to4.53) 7.39 (0.29 to p < 8722981 Patients Non-fatal MI (11.9%) 187.30)0.005 IGF1R hCV- All Fatal Coronary 11.536 0.0031 5.1641 0.0231 54/1418(3.8%) 2/59 (3.4%) 1/2 (50.0%) 0.89 (0.14 to 2.95) 25.26 (0.99 to p <0.05 8722981 Patients Heart Disease 643.88) IGF1R hCV- AllFatal/Non-fatal 7.2529 0.0266 4.8925 0.027 190/1418 14/59 (23.7%) 1/2(50.0%) 2.01 (1.05 to 3.64) 6.46 (0.26 to p < 0.05 8722981 Patients MI(def & prob) (13.4%) 163.75) IGF1R hCV- All Cardiovascular 10.19060.0061 4.8293 0.028 60/1418 (4.2%) 3/59 (5.1%) 1/2 (50.0%) 1.21 (0.29 to3.41) 22.68 (0.89 to p < 0.05 8722981 Patients Mortality 576.45) IL1AhCV- All Cardiovascular 6.9523 0.0309 5.6644 0.0173 22/739 (3.0%) 33/584(5.7%) 9/144 (6.3%) 1.95 (1.13 to 3.43) 2.17 (0.93 to 4.68) p < 0.059546471 Patients Mortality IL1A hCV- All Fatal 6.9523 0.0309 5.66440.0173 22/739 (3.0%) 33/584 (5.7%) 9/144 (6.3%) 1.95 (1.13 to 3.43) 2.17(0.93 to 4.68) p < 0.05 9546471 Patients Atherosclerotic CardiovascularDisease IL1A hCV- All History 6.1271 0.0467 5.9334 0.0149 41/739 (5.5%)39/584 (6.7%) 16/144 (11.1%) 1.22 (0.77 to 1.92) 2.13 (1.13 to 3.84) p <0.05 9546471 Patients of Congestive Heart Failure (AE) IL1B hCV- AllCardiovascular 6.6302 0.0363 6.0667 0.0138 28/886 (3.2%) 30/504 (6.0%)5/87 (5.7%) 1.94 (1.14 to 3.30) 1.87 (0.62 to 4.58) p < 0.05 9546517Patients Mortality IL1B hCV- All Fatal Atherosclerotic 6.6302 0.03636.0667 0.0138 28/886 (3.2%) 30/504 (6.0%) 5/87 (5.7%) 1.94 (1.14 to3.30) 1.87 (0.62 to 4.58) p < 0.05 9546517 Patients CardiovascularDisease IL4R hCV- All Fatal CHD/Definite 10.0029 0.0067 6.8027 0.009163/471 (13.4%) 99/691 (14.3%) 23/313 (7.3%) 1.08 (0.77 to 1.53) 0.51(0.31 to 0.84) p < 0.05 2769554 Patients Non-fatal MI IL4R hCV- AllFatal/Non-fatal 8.0376 0.018 7.0306 0.008 73/471 (15.5%) 103/691 (14.9%)28/313 (8.9%) 0.96 (0.69 to 1.33) 0.54 (0.33 to 0.84) p < 0.05 2769554Patients MI (def & prob) ITGAE hCV- All Coronary Artery 7.2966 0.0266.6147 0.0101 165/869 94/502 (18.7%) 29/96 (30.2%) 0.98 (0.74 to 1.30)1.85 (1.14 to 2.92) p < 0.05 22273204 Patients Bypass (19.0%) orRevascularization ITGAE hCV- All Family History 7.7796 0.0204 7.0120.0081 339/869 214/502 (42.6%) 51/96 (53.1%) 1.16 (0.93 to 1.45) 1.77(1.16 to 2.71) p < 0.05 22273204 Patients of CV Disease (39.0%) ITGB2hCV- All Fatal/Non-fatal 6.3122 0.0426 4.9703 0.0258 40/648 (6.2%)39/645 (6.0%) 20/180 (11.1%) 0.98 (0.62 to 1.54) 1.90 (1.06 to 3.30) p <0.05 1088055 Patients Cerebrovascular Disease KL hCV- All TotalMortality 9.639 0.0081 8.3919 0.0038 62/1079 (5.7%) 24/364 (6.6%) 6/31(19.4%) 1.16 (0.70 to 1.86) 3.94 (1.42 to 9.37) p < 2983035 Patients0.005 LAMA2 hCV- All Congestive 7.5478 0.023 4.4464 0.035 70/1058 (6.6%)37/379 (9.8%) 6/38 (15.8%) 1.53 (1.00 to 2.30) 2.65 (0.97 to 6.13) p <0.05 25990513 Patients Heart Failure LAMB2 hCV- All Congestive 10.14030.0063 6.2037 0.0127 102/1351 9/117 (7.7%) 2/4 (50.0%) 1.02 (0.47 to1.97) 12.23 (1.46 to p < 0.05 25630499 Patients Heart Failure (7.5%)102.87) LBP hCV- All Fatal CHD/Definite 6.4704 0.0394 4.2567 0.0391148/1262 33/194 (17.0%) 3/11 (27.3%) 1.54 (1.01 to 2.30) 2.82 (0.61 to9.88) p < 0.05 25617571 Patients Non-fatal MI (11.7%) LBP hCV- All FatalCoronary 13.1539 0.0014 6.9038 0.0086 41/1262 (3.2%) 14/194 (7.2%) 2/11(18.2%) 2.32 (1.20 to 4.23) 6.62 (0.99 to p < 0.05 25617571 PatientsHeart Disease 26.71) LBP hCV- All Total Mortality 7.0693 0.0292 4.45860.0347 73/1262 (5.8%) 19/194 (9.8%) 2/11 (18.2%) 1.77 (1.02 to 2.94)3.62 (0.55 to p < 0.05 25617571 Patients 14.37) LBP hCV- AllCardiovascular 9.7674 0.0076 4.7106 0.03 48/1262 (3.8%) 14/194 (7.2%)2/11 (18.2%) 1.97 (1.03 to 3.55) 5.62 (0.84 to p < 0.05 25617571Patients Mortality 22.56) LBP hCV- All Fatal Atherosclerotic 9.76740.0076 4.7106 0.03 48/1262 (3.8%) 14/194 (7.2%) 2/11 (18.2%) 1.97 (1.03to 3.55) 5.62 (0.84 to p < 0.05 25617571 Patients Cardiovascular 22.56)Disease LPA hCV- All Fatal/Non-fatal 6.1113 0.0134 5.7793 0.0162 89/1393(6.4%) 10/72 (13.9%) 0/0 (0.0%) 2.36 (1.11 to 4.57) p < 0.05 25930271Patients Cerebrovascular Disease LPA hCV- All History of Stroke 10.37480.0013 8.9305 0.0028 31/1393 (2.2%) 6/72 (8.3%) 0/0 (0.0%) 4.00 (1.46 to9.28) p < 25930271 Patients 0.005 LPA hCV- All Any report of 8.10230.0044 7.5172 0.0061 79/1393 (5.7%) 10/72 (13.9%) 0/0 (0.0%) 2.68 (1.25to 5.22) p < 0.05 25930271 Patients Stroke Prior to or During CARE LRP8hCV- All Hosp. for 6.2202 0.0446 5.3814 0.0204 83/557 (14.9%) 130/687(18.9%) 51/235 (21.7%) 1.33 (0.99 to 1.81) 1.58 (1.07 to 2.33) p < 0.05190754 Patients Unstable Angina LRP8 hCV- All History of Coronary15.2786 0.0005 14.3188 0.0002 120/557 214/687 (31.1%) 57/235 (24.3%)1.65 (1.27 to 2.14) 1.17 (0.81 to 1.67) p < 190754 Patients ArteryBypass Graft (21.5%) 0.0005 LTA hCV- All Coronary 6.3807 0.0412 5.01480.0251 243/1259 38/199 (19.1%) 4/7 (57.1%) 0.99 (0.67 to 1.43) 5.57(1.22 to p < 0.05 16172087 Patients Artery Bypass (19.3%) 28.45) orRevascularization MARCO hCV- All Hosp. for 9.4031 0.0091 4.6978 0.302601/1286 85/161 (52.8%) 1/12 (8.3%) 1.28 (0.92 to 1.77) 0.10 (0.01 to0.54) p < 0.05 2126249 Patients Cardiovascular (46.7%) Disease MARCOhCV- All Total Cardiovascular 9.8232 0.0074 4.9202 0.265 618/1286 87/161(54.0%) 1/12 (8.3%) 1.27 (0.92 to 1.77) 0.10 (0.01 to 0.51) p < 0.052126249 Patients Disease Events (48.1%) MC1R hCV- All Hosp. for 7.40680.0246 5.6448 0.0175 232/1310 28/161 (17.4%) 4/7 (57.1%) 0.98 (0.62 to1.49) 6.19 (1.36 to p < 0.05 11951095 Patients Unstable Angina (17.7%)31.62) MMP27 hCV- All History of 7.9408 0.0189 7.7188 0.0055 314/1006125/381 (32.8%) 38/82 (46.3%) 1.08 (0.84 to 1.38) 1.90 (1.20 to 3.00) p< 0.05 1366366 Patients Percutaneous (31.2%) Transluminal CoronaryAngioplasty MSR1 hCV- All Fatal CHD/Definite 6.6741 0.0355 4.5804 0.0323165/1304 16/157 (10.2%) 3/7 (42.9%) 0.78 (0.44 to 1.31) 5.18 (1.01 to p< 0.05 16172249 Patients Non-fatal MI (12.7%) 23.68) MSR1 hCV- All FatalCoronary 13.1069 0.0014 7.1248 0.0076 52/1304 (4.0%) 3/157 (1.9%) 2/7(28.6%) 0.47 (0.11 to 1.29) 9.63 (1.36 to p < 0.05 16172249 PatientsHeart Disease 45.84) MSR1 hCV- All Cardiovascular 10.3616 0.0056 6.55010.0105 57/1304 (4.4%) 5/157 (3.2%) 2/7 (28.6%) 0.72 (0.25 to 1.66) 8.75(1.24 to p < 0.05 16172249 Patients Mortality 41.56) MSR1 hCV- All FatalAtherosclerotic 10.3616 0.0056 6.5501 0.0105 57/1304 (4.4%) 5/157 (3.2%)2/7 (28.6%) 0.72 (0.25 to 1.66) 8.75 (1.24 to p < 0.05 16172249 PatientsCardiovascular 41.56) Disease MTHFD1 hCV- All Hosp. for Peripheral7.6444 0.0219 6.96 0.0083 6443 (1.4%) 22/732 (3.0%) 14/291 (4.8%) 2.26(0.97 to 6.17) 3.68 (1.46 to p < 0.05 1376137 Patients Arterial Disease10.50) MTHFR hCV- All Congestive 6.0848 0.0477 5.4632 0.0194 56/650(8.6%) 52/667 (7.8%) 4/149 (2.7%) 0.90 (0.60 to 1.33) 0.29 (0.09 to0.73) p < 0.05 1202883 Patients Heart Failure MYH11 hCV334226 All FatalCHD/Definite 6.8287 0.0329 4.0068 0.0453 103/938 71/485 (14.6%) 11/55(20.0%) 1.39 (1.00 to 1.92) 2.03 (0.97 to 3.91) p < 0.05 PatientsNon-fatal MI (11.0%) MYH11 hCV334226 All Non-fatal MI 9.5875 0.00837.7575 0.0053 102/938 68485 (14.0%) 13/55 (23.6%) 1.34 (0.96 to 1.85)2.54 (1.27 to 4.76) p < 0.05 Patients (def & prob) (10.9%) MYH11hCV334226 All Fatal/Non-fatal 7.4812 0.0237 5.5795 0.0182 116/938 76485(15.7%) 13/55 (23.6%) 1.32 (0.96 to 1.80) 2.19 (1.10 to 4.10) p < 0.05Patients MI (def & prob) (12.4%) MYH11 hCV334226 All CARE MI: 10.0880.0064 7.3943 0.0065 616/938 293/485 (60.4%) 26/55 (47.3%) 0.80 (0.64 to1.00) 0.47 (0.27 to 0.81) p < 0.05 Patients Q-Wave MI (65.7%) NOS2A hCV-All Total Coronary Heart 8.4422 0.0147 6.5846 0.0103 340/980 165/445(37.1%) 9/53 (17.0%) 1.11 (0.88 to 1.40) 0.39 (0.17 to 0.76) p < 0.0511889257 Patients Disease Events (34.7%) NOS2A hCV- All Fatal/Non-fatal6.5972 0.0369 5.927 0.0149 390/980 181/445 (40.7%) 12/53 (22.6%) 1.04(0.83 to 1.30) 0.44 (0.22 to 0.83) p < 0.05 11889257 PatientsAtherosclerotic (39.8%) CV Disease NPC1 hCV- All Hosp. for 14.10280.0009 13.6581 0.0002 244/560 323/697 (46.3%) 122/208 (58.7%) 1.12 (0.89to 1.40) 1.84 (1.33 to 2.54) p < 25472673 Patients Cardiovascular(43.6%) 0.0005 Disease NPC1 hCV- All Total Coronary Heart 6.9104 0.03166.8509 0.0089 180/560 242/697 (34.7%) 88/208 (42.3%) 1.12 (0.89 to 1.42)1.55 (1.12 to 2.15) p < 0.05 25472673 Patients Disease Events (32.1%)NPC1 hCV- All Total Cardiovascular 13.7798 0.001 13.0217 0.0003 254/560330/697 (47.3%) 125/208 (60.1%) 1.08 (0.87 to 1.35) 1.81 (1.32 to 2.51)p < 25472673 Patients Disease Events (45.4%) 0.0005 NPC1 hCV- AllFatal/Non-fatal 9.3597 0.0093 9.2405 0.0024 204/560 274/697 (39.3%)101/208 (48.6%) 1.13 (0.90 to 1.42) 1.65 (1.19 to 2.27) p < 25472673Patients Atherosclerotic (36.4%) 0.005 CV Disease P2RY4 hCV- All FatalCHD/Definite 6.9422 0.0311 5.1647 0.023 147/1231 34234 (14.5%) 4/11(36.4%) 1.25 (0.83 to 1.85) 4.21 (1.09 to p < 0.05 8815434 PatientsNon-fatal MI (11.9%) 14.13) P2RY4 hCV- All Fatal Coronary 6.7934 0.03355.0538 0.0246 44/1231 (3.6%) 11/234 (4.7%) 2/11 (18.2%) 1.33 (0.64 to2.52) 6.00 (0.90 to p < 0.05 8815434 Patients Heart Disease 24.13) P2RY4hCV- All Cardiovascular 7.1799 0.0276 4.5705 0.0325 48/1231 (3.9%)14/234 (6.0%) 2/11 (18.2%) 1.57 (0.82 to 2.82) 5.48 (0.82 to p < 0.058815434 Patients Mortality 21.98) P2RY4 hCV- All Fatal Atherosclerotic7.1799 0.0276 4.5705 0.0325 48/1231 (3.9%) 14/234 (6.0%) 2/11 (18.2%)1.57 (0.82 to 2.82) 5.48 (0.82 to p < 0.05 8815434 PatientsCardiovascular 21.98) Disease PDGFRA hCV- All Fatal CHD/Definite 16.94860.0002 13.3442 0.0003 140/1161 36/288 (12.5%) 8/18 (44.4%) 1.04 (0.70 to1.53) 5.83 (2.19 to p < 22271841 Patients Non-fatal MI (12.1%) 15.04)0.0005 PDGFRA hCV- All Non-fatal MI 11.957 0.0025 9.9467 0.0016 138/116137288 (12.8%) 7/18 (38.9%) 1.09 (0.73 to 1.60) 4.72 (1.71 to p <22271841 Patients (def & prob) (11.9%) 12.18) 0.005 PDGFRA hCV- AllFatal/Non-fatal 10.0356 0.0066 8.4264 0.0037 154/1161 43288 (14.9%) 7/18(38.9%) 1.15 (0.79 to 1.64) 4.16 (1.51 to p < 22271841 Patients MI (def& prob) (13.3%) 10.73) 0.005 PEMT hCV- All Fatal/Non-fatal 6.0125 0.04955.466 0.0194 193/462 299/739 (40.5%) 91/275 (33.1%) 0.95 (0.75 to 1.20)0.69 (0.50 to 0.94) p < 0.05 7443062 Patients Atherosclerotic (41.8%) CVDisease PLA2G4C hCV- All Congestive 9.2587 0.0098 4.6217 0.0316 95/1334(7.1%) 15/127 (11.8%) 2/6 (33.3%) 1.75 (0.95 to 3.03) 6.53 (0.90 to p <0.05 16196014 Patients Heart Failure 33.85) PLA2G7 hCV- AllFatal/Non-fatal 20.7612 <.0001 18.7233 <.0001 42/834 (5.0%) 41/534(7.7%) 17/101 (16.8%) 1.57 (1.00 to 2.45) 3.82 (2.04 to 6.90) p <7582933 Patients Cerebrovascular 0.0005 Disease PLA2G7 hCV- All AnyReport of 7.7866 0.0204 5.2256 0.0223 39/834 (4.7%) 41/534 (7.7%) 10/101(9.9%) 1.70 (1.08 to 2.67) 2.24 (1.03 to 4.47) p < 0.05 7582933 PatientsStroke Prior to or During CARE PLA2G7 hCV- All Any Report of 13.90460.001 10.3804 0.0013 21/834 (2.5%) 29/534 (5.4%) 9/101 (8.9%) 2.22 (1.26to 3.99) 3.79 (1.61 to 8.28) p < 7582933 Patients Stroke During CARE0.005 PLA2G7 hCV- All 1st Stroke Occurred 18.5501 < .0001 13.9535 0.000216/834 (1.9%) 27/534 (5.1%) 9/101 (8.9%) 2.72 (1.47 to 5.21) 5.00 (2.07to p < 7582933 Patients During CARE 11.43) 0.0005 PLAT hCV- All Hosp.for 6.4904 0.039 6.3891 0.0115 548/1125 132/324 (40.7%) 10/20 (50.0%)0.72 (0.56 to 0.93) 1.05 (0.43 to 2.59) p < 0.05 3212009 PatientsCardiovascular (48.7%) Disease PLAT hCV- All Hosp. for 6.0758 0.04795.9512 0.0147 216/1125 43/324 (13.3%) 4/20 (20.0%) 0.64 (0.45 to 0.91)1.05 (0.30 to 2.90) p < 0.05 3212009 Patients Unstable Angina (19.2%)PLAT hCV- All Total Coronary 7.506 0.0234 7.4548 0.0063 412/1125 92/324(28.4%) 7/20 (35.0%) 0.69 (0.52 to 0.90) 0.93 (0.35 to 2.29) p < 0.053212009 Patients Heart Disease Events (36.6%) PLAT hCV- All TotalCardiovascular 6.7267 0.0346 6.675 0.0098 564/1125 136/324 (42.0%) 10/20(50.0%) 0.72 (0.56 to 0.92) 1.00 (0.41 to 2.44) p < 0.05 3212009Patients Disease Events (50.1%) PLAT hCV- All Fatal/Non-fatal 8.8140.0122 8.5038 0.0035 466/1125 105/324 (32.4%) 9/20 (45.0%) 0.68 (0.52 to0.88) 1.16 (0.46 to 2.82) p < 3212009 Patients Atherosclerotic (41.4%)0.005 CV Disease PLAT hCV- All CARE MI: 6.2617 0.0437 4.8823 0.027171/1125 202/324 (62.3%) 18/20 (90.0%) 0.96 (0.75 to 1.24) 5.22 (1.50 top < 0.05 3212009 Patients Q-Wave MI (63.3%) 32.94) PLAU hCV- All Hosp.for Peripheral 7.0124 0.03 6.2128 0.0127 22/888 (2.5%) 14/499 (2.8%)6/78 (7.7%) 1.14 (0.56 to 2.22) 3.28 (1.18 to 7.88) p < 0.05 16273460Patients Arterial Disease PLG hCV- All Hosp. for Peripheral 6.55290.0378 5.2289 0.0222 14/738 (1.9%) 22/622 (3.5%) 6/105 (5.7%) 1.90 (0.97to 3.82) 3.13 (1.09 to 8.01) p < 0.05 25614474 Patients Arterial DiseasePON1 hCV- All History of Stroke 7.762 0.0206 6.2747 0.0122 28/753 (3.7%)8/579 (1.4%) 2/133 (1.5%) 3.36 (0.15 to 0.77) 0.40 (0.06 to 1.34) p <0.05 2548962 Patients PON1 hCV- All Any Report of Stroke 18.3981 0.000115.8161 <.0001 16/753 (2.1%) 39/579 (6.7%) 4/133 (3.0%) 3.33 (1.88 to6.18) 1.43 (0.40 to 3.97) p < 2548962 Patients During CARE 0.0005 PON1hCV- All 1st Stroke Occurred 15.5223 0.0004 13.6541 0.0002 14/753 (1.9%)34/579 (5.9%) 4/133 (3.0%) 3.29 (1.79 to 6.40) 1.64 (0.46 to 4.65) p <2548962 Patients During CARE 0.0005 PRKCQ hCV- All Fatal CHD/Definite7.6114 0.0222 6.3909 0.0115 114/817 65/546 (11.9%) 5/106 (4.7%) 0.83(0.60 to 1.15) 0.31 (0.11 to 0.69) p < 0.05 15954277 Patients Non-fatalMI (14.0%) PRKCQ hCV- All History of 7.1755 0.0277 6.1643 0.013 248/817201/546 (36.8%) 30/106 (28.3%) 1.34 (1.06 to 1.68) 0.91 (0.57 to 1.40) p< 0.05 15954277 Patients Percutaneous (30.4%) Transluminal CoronaryAngioplasty PROCR hCV- All Congestive 8.8085 0.0122 7.09 0.0078 90/1206(7.5%) 18/248 (7.3%) 4/14 (28.6%) 0.97 (0.56 to 1.60) 4.96 (1.34 to p <0.05 25620145 Patients Heart Failure 15.16) PROCR hCV- All Hosp. forPeripheral 18.4984 <.0001 12.2481 0.0005 30/1206 (2.5%) 9/248 (3.6%)3/14 (21.4%) 1.48 (0.65 to 3.03) 10.69 (2.33 to p < 25620145 PatientsArterial Disease 36.38) 0.005 PROCR hCV- All History 7.8606 0.01963.8993 0.0483 83/1206 (6.9%) 10/248 (4.0%) 3/14 (21.4%) 0.57 (0.27 to1.06) 3.69 (0.82 to p < 0.05 25620145 Patients of Congestive HeartFailure (AE) 12.09) PROCR hCV- All History of Diabetes 10.7224 0.00477.0162 0.0081 181/1206 29/248 (11.7%) 6/14 (42.9%) 0.75 (0.49 to 1.12)4.25 (1.38 to p < 0.05 25620145 Patients (15.0%) 12.35) PROCR hCV- AllMore Than 9.2085 0.01 7.533 0.0061 173/1206 40/248 (16.1%) 6/14 (42.9%)1.15 (0.78 to 1.66) 4.48 (1.46 to p < 0.05 25620145 Patients 1 Prior MI(14.3%) 13.03) PROCR hCV- All Hosp. for Peripheral 8.569 0.0138 6.14060.0132 30/1200 (2.5%) 9/248 (3.6%) 2/13 (15.4%) 1.47 (0.65 to 3.01) 7.09(1.07 to p < 0.05 7499900 Patients Arterial Disease 27.93) PROCR hCV-All More Than 6.3048 0.0427 5.2347 0.0221 172/1200 40/248 (16.1%) 5/13(38.5%) 1.15 (0.78 to 1.66) 3.74 (1.12 to p < 0.05 7499900 Patients 1Prior MI (14.3%) 11.33) PSMB9 hCV- All Hosp. for 6.1961 0.0451 4.82940.028 153/773 99/595 (16.6%) 12/110 (10.9%) 0.81 (0.61 to 1.07) 0.50(0.25 to 0.89) p < 0.05 8849004 Patients Unstable Angina (19.8%) SCARF1hCV- All Congestive 7.751 0.0207 7.3777 0.0066 94/1070 (8.8%) 16/369(4.3%) 2/30 (6.7%) 0.47 (0.26 to 0.79) 0.74 (0.12 to 2.52) p < 0.0525613493 Patients Heart Failure SCARF1 hCV- All History of Stroke10.3312 0.0057 7.0201 0.0081 21/1070 (2.0%) 14/369 (3.8%) 3/30 (10.0%)1.97 (0.97 to 3.88) 5.55 (1.26 to p < 0.05 25613493 Patients 17.38) SELLhCV- All Congestive 10.7046 0.0047 9.2061 0.0024 78/1074 (7.3%) 27/362(7.5%) 7/30 (23.3%) 1.03 (0.64 to 1.60) 3.89 (1.50 to 8.91) p < 16172571Patients Heart Failure 0.005 SELL hCV- All History of 6.4757 0.03924.5067 0.0338 197/1074 85/362 (23.5%) 9/30 (30.0%) 1.37 (1.02 to 1.82)1.91 (0.82 to 4.11) p < 0.05 16172571 Patients Angina Pectoris (18.3%)SELL hCV- All Congestive 10.9187 0.0043 9.3741 0.0022 77/1073 (7.2%)27/365 (7.4%) 7/30 (23.3%) 1.03 (0.65 to 1.61) 3.94 (1.52 to 9.03) p <25474627 Patients Heart Failure 0.005 SELL hCV- All History of 6.15730.046 4.1763 0.041 197/1073 85/365 (23.3%) 9/30 (30.0%) 1.35 (1.01 to1.80) 1.91 (0.82 to 4.10) p < 0.05 25474627 Patients Angina Pectoris(18.4%) SELP hCV- All Coronary 7.9917 0.0184 5.884 0.0153 205/996 78/422(18.5%) 2/47 (4.3%) 0.88 (0.65 to 1.17) 0.17 (0.03 to 0.56) p < 0.0511975296 Patients Artery Bypass (20.6%) or Revascularization SER- hCV-All Fatal/Non-fatal 8.1188 0.0173 7.4562 0.0063 53/915 (5.8%) 36/486(7.4%) 11/79 (13.9%) 1.30 (0.83 to 2.01) 2.63 (1.25 to 5.10) p < 0.05PINA1 1260328 Patients Cerebrovascular Disease SER- hCV- All Hosp. forPeripheral 6.8119 0.0091 5.6794 0.0172 39/1451 (2.7%) 3/27 (11.1%) 0/0(0.0%) 4.53 (1.05 to 13.67) p < 0.05 PINA10 15943710 Patients ArterialDisease SER- hCV- All Fatal Coronary 9.6621 0.008 8.2548 0.0041 24/407(5.9%) 28/724 (3.9%) 5/338 (1.5%) 0.64 (0.37 to 1.13) 0.24 (0.08 to0.59) p < PINA3 2188895 Patients Heart Disease 0.005 SER- hCV- AllCardiovascular 13.1924 0.0014 10.5191 0.0012 28/407 (6.9%) 30/724 (4.1%)5/338 (1.5%) 0.59 (0.34 to 1.00) 0.20 (0.07 to 0.49) p < PINA3 2188895Patients Mortality 0.005 SER- hCV- All Fatal 13.1924 0.0014 10.51910.0012 28/407 (6.9%) 30/724 (4.1%) 5/338 (1.5%) 0.59 (0.34 to 1.00) 0.20(0.07 to 0.49) p < PINA3 2188895 Patients Atherosclerotic Cardiovascular0.005 Disease SER- hCV- All History 7.4219 0.0245 7.0093 0.0081 70/407(17.2%) 112/724 (15.5%) 35/338 (10.4%) 0.88 (0.64 to 1.23) 0.56 (0.36 to0.85) p < 0.05 PINA3 2188895 Patients of Diabetes SER- hCV- All MoreThan 1 8.7112 0.0128 8.6032 0.0034 77/407 (18.9%) 90/724 (12.4%) 50/338(14.8%) 0.61 (0.44 to 0.85) 0.74 (0.50 to 1.10) p < PINA3 2188895Patients Prior MI 0.005 SER- hCV- All Fatal Coronary 6.1008 0.04735.8986 0.0152 26/893 (2.9%) 28/503 (5.6%) 3/70 (4.3%) 1.97 (1.14 to3.41) 1.49 (0.35 to 4.38) p < 0.05 PINB2 8931357 Patients Heart DiseaseSER- hCV- All 1st Stroke Occurred 6.4019 0.0407 5.3677 0.0205 23/893(2.6%) 25/503 (5.0%) 4/70 (5.7%) 1.98 (1.11 to 3.54) 2.29 (0.66 to 6.18)p < 0.05 PINB2 8931357 Patients During CARE SMTN hCV- AllFatal/Non-fatal 6.1622 0.0459 4.8023 0.0284 70/617 (11.3%) 104/669(15.5%) 30/178 (16.9%) 1.44 (1.04 to 2.00) 1.58 (0.98 to 2.50) p < 0.0525627634 Patients MI (def & prob) SREBF2 hCV- All Non-fatal MI 6.58330.0372 4.1648 0.0413 149/1263 30/196 (15.3%) 3/8 (37.5%) 1.35 (0.87 to2.04) 4.49 (0.91 to p < 0.05 16170982 Patients (def & prob) (11.8%)18.47) SREBF2 hCV- All CARE MI: 6.4495 0.0398 3.9908 0.0457 797/1263132/196 (67.3%) 2/8 (25.0%) 1.21 (0.88 to 1.67) 0.20 (0.03 to 0.85) p <0.05 16170982 Patients Q-Wave MI (63.1%) TAP1 hCV- All Congestive15.1025 0.0005 6.8656 0.0088 102/1379 7/92 (7.6%) 2/3 (66.7%) 1.03 (0.42to 2.14) 25.04 (2.38 to p < 0.05 25630686 Patients Heart Failure (7.4%)541.07) TGFB1 hCV- All Cardiovascular 6.3933 0.0409 5.0113 0.0252 20/686(2.9%) 34/629 (5.4%) 10/162 (6.2%) 1.90 (1.09 to 3.40) 2.19 (0.97 to4.67) p < 0.05 8708473 Patients Mortality TGFB1 hCV- All Fatal 6.39330.0409 5.0113 0.0252 20/686 (2.9%) 34/629 (5.4%) 10/162 (6.2%) 1.90(1.09 to 3.40) 2.19 (0.97 to 4.67) p < 0.05 8708473 PatientsAtherosclerotic Cardiovascular Disease TGFB1 hCV- All More Than 10.12950.0063 8.4288 0.0037 81/686 (11.8%) 110/629 (17.5%) 30/162 (18.5%) 1.58(1.16 to 2.16) 1.70 (1.06 to 2.66) p < 8708473 Patients 1 Prior MI 0.005TGFB1 hCV- All Any Report of Stroke 8.1211 0.0172 6.0819 0.0137 24/686(3.5%) 21/629 (3.3%) 13/162 (8.0%) 0.95 (0.52 to 1.73) 2.41 (1.17 to4.76) p < 0.05 8708473 Patients During CARE TGFB1 hCV- All 1st StrokeOccurred 8.5461 0.0139 6.7848 0.0092 20/686 (2.9%) 19/629 (3.0%) 12/162(7.4%) 1.04 (0.55 to 1.97) 2.66 (1.24 to 5.50) p < 0.05 8708473 PatientsDuring CARE THBD hCV- All Fatal CHD/Definite 10.6922 0.0048 8.09190.0044 113/1025 58/394 (14.7%) 12/48 (25.0%) 1.39 (0.99 to 1.95) 2.69(1.31 to 5.18) p < 2531431 Patients Non-fatal MI (11.0%) 0.005 THBD hCV-All Coronary 7.5952 0.0224 7.1945 0.0073 180/1025 94394 (23.9%) 11/48(22.9%) 1.47 (1.11 to 1.95) 1.40 (0.67 to 2.70) p < 0.05 2531431Patients Artery Bypass (17.6%) or Revascularization THBD hCV- AllHistory of 12.6379 0.0018 10.8371 0.001 315/1025 137/394 (34.8%) 26/48(54.2%) 1.20 (0.94 to 1.54) 2.66 (1.49 to 4.81) p < 2531431 PatientsPercutaneous (30.7%) 0.005 Transluminal Coronary Angioplasty THBS1 hCV-All Coronary 11.2439 0.0036 8.8265 0.003 217/1194 67/254 (26.4%) 1/18(5.6%) 1.61 (1.17 to 2.20) 0.27 (0.02 to 1.30) p < 16170900 PatientsArtery Bypass (18.2%) 0.005 or Revascularization THBS1 hCV- All Historyof 10.3425 0.0057 8.823 0.003 233/1194 50/254 (19.7%) 9/18 (50.0%) 1.01(0.71 to 1.41) 4.12 (1.59 to p < 16170900 Patients Angina Pectoris(19.5%) 10.68) 0.005 TIMP2 hCV- All Fatal CHD/Definite 9.2264 0.00996.5997 0.0102 45/451 (10.0%) 109/715 (15.2%) 30/300 (10.0%) 1.62 (1.13to 2.37) 1.00 (0.61 to 1.62) p < 0.05 1466546 Patients Non-fatal MITIMP2 hCV- All Family History 6.153 0.0461 6.1285 0.0133 168/451 294/715(41.1%) 139/300 (46.3%) 1.18 (0.92 to 1.50) 1.45 (1.08 to 1.96) p < 0.051466546 Patients of CV Disease (37.3%) TLR5 hCV- All Coronary 8.0720.0177 7.2739 0.007 199/1070 76/371 (20.5%) 12/31 (38.7%) 1.13 (0.84 to1.51) 2.76 (1.29 to 5.72) p < 0.05 15871020 Patients Artery Bypass(18.6%) or Revascularization TLR5 hCV- All Total Coronary 8.5656 0.01387.3782 0.0066 360/1070 136/371 (36.7%) 18/31 (58.1%) 1.14 (0.89 to 1.46)2.73 (1.33 to 5.75) p < 0.05 15871020 Patients Heart Disease (33.6%)Events TLR5 hCV- All Total 6.1316 0.0466 4.8612 0.0275 504/1070 188/371(50.7%) 21/31 (67.7%) 1.15 (0.91 to 1.46) 2.36 (1.13 to 5.27) p < 0.0515871020 Patients Cardiovascular Disease Events (47.1%) TLR5 hCV- AllFatal/Non-fatal 7.0226 0.0299 6.2028 0.0128 411/1070 152/371 (41.0%)19/31 (61.3%) 1.11 (0.87 to 1.42) 2.54 (1.23 to 5.43) p < 0.05 15871020Atherosclerotic (38.4%) Patients CV Disease TNF hCV- All Total Mortality8.8535 0.012 6.0624 0.0138 56/1036 (5.4%) 33/411 (8.0%) 5/30 (16.7%)1.53 (0.97 to 2.37) 3.50 (1.15 to 8.79) p < 0.05 7514879 Patients TNFhCV- All Hosp. for 8.6699 0.0131 7.5339 0.0061 483/1036 188/411 (45.7%)22/30 (73.3%) 0.97 (0.77 to 1.21) 3.15 (1.44 to 7.60) p < 0.05 7514879Patients Cardiovascular (46.6%) Disease TNF hCV- All Total 7.8468 0.01986.789 0.0092 498/1036 193/411 (47.0%) 22/30 (73.3%) 0.96 (0.76 to 1.20)2.97 (1.36 to 7.17) p < 0.05 7514879 Patients Cardiovascular (48.1%)Disease Events TNF hCV- All CARE MI: 7.9203 0.0191 5.6008 0.018 673/1036248/411 (60.3%) 13/30 (43.3%) 0.82 (0.65 to 1.04) 0.41 (0.19 to 0.86) p< 0.05 7514879 Patients Q-Wave MI (65.0%) TNFRSF- hCV- All TotalMortality 7.7139 0.0211 6.2178 0.0126 19/448 (4.2%) 57/710 (8.0%) 16/317(5.0%) 1.97 (1.18 to 3.44) 1.20 (0.60 to 2.37) p < 0.05 10A 12102850Patients TNFRSF- hCV- All More Than 6.6427 0.0361 4.852 0.0276 56/448(12.5%) 123/710 (17.3%) 40/317 (12.6%) 1.47 (1.05 to 2.08) 1.01 (0.65 to1.56) p < 0.05 10A 12102850 Patients 1 Prior MI TNFRSF- hCV- All AnyReport of Stroke 10.989 0.0041 9.6137 0.0019 74/48 (1.6%) 33/710 (4.6%)19/317 (6.0%) 3.07 (1.43 to 7.62) 4.02 (1.74 to p < 10A 12102850Patients During CARE 10.39) 0.005 TNFRSF- hCV- All 1st Stroke Occurred15.4596 0.0004 12.4232 0.0004 44/48 (0.9%) 29/710 (4.1%) 19/317 (6.0%)4.73 (1.85 to 16.02) 7.08 (2.63 to p < 10A 12102850 Patients During CARE24.59) 0.0005 VWF hCV- All Fatal Coronary 10.8514 0.0044 8.2057 0.004246/1351 (3.4%) 10/110 (9.1%) 1/7 (14.3%) 2.84 (1.32 to 5.57) 4.73 (0.25to p < 8921137 Patients Heart Disease 28.47) 0.005 VWF hCV- AllFatal/Non-fatal 7.2772 0.0263 4.3481 0.0371 87/1351 (6.4%) 11/110(10.0%) 2/7 (28.6%) 1.61 (0.79 to 3.00) 5.81 (0.82 to p < 0.05 8921137Patients Cerebrovascular 27.39) Disease VWF hCV- All Cardiovascular8.1772 0.0168 6.1886 0.0129 53/1351 (3.9%) 10/110 (9.1%) 1/7 (14.3%)2.45 (1.14 to 4.76) 4.08 (0.21 to p < 0.05 8921137 Patients Mortality24.49) VWF hCV- All Fatal Atherosclerotic 8.1772 0.0168 6.1886 0.012953/1351 (3.9%) 10/110 (9.1%) 1/17 (14.3%) 2.45 (1.14 to 4.76) 4.08 (0.21to p < 0.05 8921137 Patients Cardiovascular 24.49) Disease WWOX hCV- AllFatal/Non-fatal 9.8699 0.0072 5.7737 0.0163 89/1305 (6.8%) 8/167 (4.8%)2/5 (40.0%) 0.69 (0.30 to 1.36) 9.11 (1.19 to p < 0.05 25654217 PatientsCerebrovascular 55.63) Disease WWOX hCV- All Any Report 10.3168 0.00586.5212 0.0107 78/1305 (6.0%) 9/167 (5.4%) 2/5 (40.0%) 0.90 (0.41 to1.73) 10.49 (1.37 to p < 0.05 25654217 Patients of Stroke Prior 64.15)to or During CARE WWOX hCV- All Any Report of Stroke 17.6324 0.00019.1628 0.0025 51/1305 5/167 (3.0%) 2/5 (40.0%) 0.76 (0.26 to 1.76) 16.39(2.13 to p < 25654217 Patients During CARE (3.9%) 100.97) 0.005 WWOXhCV- All 1st Stroke Occurred 21.4279 <.0001 9.8532 0.0017 46/1305 3/167(1.8%) 2/5 (40.0%) 0.50 (0.12 to 1.39) 18.25 (2.36 to p < 25654217Patients During CARE (3.5%) 112.63) 0.005 WWOX hCV- All Total CoronaryHeart 6.3913 0.0409 6.2902 0.0121 149/479 253/718 (35.2%) 113/282(40.1%) 1.21 (0.94 to 1.54) 1.48 (1.09 to 2.01) p < 0.05 57888 PatientsDisease Events (31.1%) WWOX hCV- All Fatal/Non-fatal 7.3501 0.02537.2682 0.007 170/479 286/718 (39.8%) 128/282 (45.4%) 1.20 (0.95 to 1.53)1.51 (1.12 to 2.04) p < 0.05 57888 Patients Atherosclerotic (35.5%) CVDisease ABCC6 hCV- All Definite Nonfatal MI 6.4478 0.0111 6.0215 0.0141128/1408 9/44 (20.5%) 2.57 (1.14 to 5.25) p < 0.05 25620774 Patients(9.1%) ABCC6 hCV- All Fatal CHD/ 4.3789 0.0364 4.1898 0.0407 171/140810/44 (22.7%) 2.13 (0.98 to 4.23) p < 0.05 25620774 Patients DefiniteNonfatal MI (12.1%) ABCC6 hCV- All CARE MI: 6.0048 0.0143 5.7616 0.0164895/1408 20/44 (45.5%) 0.48 (0.26 to 0.87) p < 0.05 25620774 PatientsQ-Wave MI (63.6%) ABO hCV- All MI (Fatal/Nonfatal) 6.5033 0.0387 5.53590.0186 136/856 62/545 (11.4%) 8/77 (10.4%) 0.61 (0.27 to 1.23) 0.68(0.49 to 0.93) p < 0.05 25620774 Patients (15.9%) ABO hCV- All FatalCHD/Definite 6.6893 0.0353 4.3471 0.0371 120/856 60/545 (11.0%) 4/77(5.2%) 0.34 (0.10 to 0.83) 0.76 (0.54 to 1.05) p < 0.05 25620774Patients Nonfatal MI (14.0%) ABO hCV- All Fatal CHD/Definite 6.72970.0346 4.7025 0.0301 119/847 61/542 (11.3%) 4/80 (5.0%) 0.32 (0.10 to0.79) 0.78 (0.56 to 1.07) p < 0.05 25610819 Patients Nonfatal MI (14.0%)ADAM- hCV- All Fatal CHD/Definite 7.5605 0.0228 6.7732 0.0093 92/873(10.5%) 79/516 (15.3%) 14/90 (15.6%) 1.56 (0.82 to 2.80) 1.53 (1.11 to2.12) p < 0.05 TS1 529710 Patients Nonfatal MI ADAM- hCV- All FatalCoronary 7.3045 0.0259 6.9927 0.0082 24/873 (2.7%) 29/516 (5.6%) 4/90(4.4%) 1.65 (0.48 to 4.38) 2.11 (1.21 to 3.69) p < 0.05 TS1 529710Patients Heart Disease ADAM- hCV- All Total Mortality 12.1574 0.002311.7126 0.0006 40/873 (4.6%) 48/516 (9.3%) 6/90 (6.7%) 1.49 (0.55 to3.36) 2.14 (1.38 to 3.31) p < TS1 529710 Patients 0.005 ADAM- hCV- AllCardiovascular 10.2172 0.006 9.7327 0.0018 26/873 (3.0%) 34/516 (6.6%)4/90 (4.4%) 1.52 (0.44 to 4.00) 2.30 (1.37 to 3.91) p < TS1 529710Patients Mortality 0.005 ADAM- hCV- All Fatal Atherosclerotic 10.21720.006 9.7327 0.0018 26/873 (3.0%) 34/516 (6.6%) 4/90 (4.4%) 1.52 (0.44to 4.00) 2.30 (1.37 to 3.91) p < TS1 529710 Patients Cardiovascular0.005 Disease ADAM- hCV- All History of Diabetes 6.9684 0.0307 6.90030.0086 112/873 93/516 (18.0%) 13/90 (14.4%) 1.15 (0.59 to 2.07) 1.49(1.11 to 2.01) p < 0.05 TS1 529710 Patients (12.8%) APOBE- hCV- AllStroke 17.213 0.0002 15.295 <.0001 32/1131 (2.8%) 25/318 (7.9%) 2/27(7.4%) 2.75 (0.43 to 9.79) 2.93 (1.70 to 5.01) p < C1 15757745 Patients0.0005 APOBE- hCV- All Percutaneous 6.9765 0.0306 5.2376 0.0221 126/113230/319 (9.4%) 7/27 (25.9%) 2.80 (1.08 to 6.45) 0.83 (0.54 to 1.24) p <0.05 15757745 Patients Transluminal (11.1%) C1 Coronary AngioplastyAPOBE- hCV- All Hosp. for 6.3026 0.0428 4.6198 0.0316 512/1132 166/319(52.0%) 16/27 (59.3%) 1.76 (0.82 to 3.94) 1.31 (1.02 to 1.69) p < 0.05C1 15757745 Patients Cardiovascular (45.2%) Disease APOBE- hCV- AllFatal/Nonfatal 11.5495 0.0031 11.1298 0.0008 63/1132 (5.6%) 35/319(11.0%) 2/27 (7.4%) 1.36 (0.22 to 4.70) 2.09 (1.34 to 3.21) p < C115757745 Patients Cerebrovascular 0.005 Disease APOBE- hCV- All Hosp.for 7.827 0.02 5.8787 0.0153 204/1132 50/319 (15.7%) 10/27 (37.0%) 2.68(1.17 to 5.84) 0.85 (0.60 to 1.18) p < 0.05 C1 15757745 PatientsUnstable Angina (18.0%) APOBE- hCV- All Total Cardiovascular 6.27450.0434 4.9393 0.0263 527/1132 171/319 (53.6%) 16/27 (59.3%) 1.67 (0.77to 3.73) 1.33 (1.03 to 1.70) p < 0.05 C1 15757745 Patients DiseaseEvents (46.6%) APOBE- hCV- All Any Report 17.6174 0.0001 13.6085 0.000253/1132 (4.7%) 33/319 (10.3%) 4/27 (14.8%) 3.54 (1.01 to 9.61) 2.35(1.49 to 3.68) p < 15757745 Patients of Stroke Prior 0.0005 C1 to orDuring CARE APOBE- hCV- All Any Report of Stroke 14.6273 0.0007 13.03370.0003 33/1132 (2.9%) 24/319 (7.5%) 2/27 (7.4%) 2.66 (0.42 to 9.47) 2.71(1.56 to 4.64) p < C1 15757745 Patients During CARE 0.0005 APOBE- hCV-All 1st Stroke Occurred 15.5685 0.0004 13.4449 0.0002 28/1132 (2.5%)22/319 (6.9%) 2/27 (7.4%) 3.15 (0.49 to 11.33) 2.92 (1.63 to 5.17) p <C1 15757745 Patients During CARE 0.0005 ASAH1 hCV- All MI(Fatal/Nonfatal) 6.5487 0.0378 6.0662 0.0138 64/397 (16.1%) 108/735(14.7%) 34/343 (9.9%) 0.57 (0.36 to 0.89) 0.90 (0.64 to 1.26) p < 0.052442143 Patients ASAH1 hCV- All Definite Nonfatal MI 7.1575 0.02796.9682 0.0083 47/397 (11.8%) 72/735 (9.8%) 21/343 (6.1%) 0.49 (0.28 to0.82) 0.81 (0.55 to 1.20) p < 0.05 2442143 Patients ASAH1 hCV- All FatalCHD/Definite 7.3794 0.025 7.0385 0.008 59/397 (14.9%) 96/735 (13.1%)29/343 (8.5%) 0.53 (0.33 to 0.84) 0.86 (0.61 to 1.23) p < 0.05 2442143Patients Nonfatal MI ASAH1 hCV- All Fatal/Nonfatal MI 6.1285 0.04675.639 0.0176 63/397 (15.9%) 107/735 (14.6%) 34/343 (9.9%) 0.58 (0.37 to0.90) 0.90 (0.65 to 1.27) p < 0.05 2442143 Patients (def & prob) BAT2hCV- All Fatal Coronary 7.3974 0.0248 6.1273 0.0133 28/796 (3.5%) 20/575(3.5%) 9/101 (8.9%) 2.68 (1.16 to 5.66) 0.99 (0.54 to 1.76) p < 0.057514692 Patients Heart Disease BAT2 hCV- All Cardiovascular 8.23650.0163 6.0975 0.0135 33/796 (4.1%) 21/575 (3.7%) 10/101 (9.9%) 2.54(1.15 to 5.15) 0.88 (0.49 to 1.52) p < 0.05 7514692 Patients MortalityBAT2 hCV- All Fatal Atherosclerotic 8.2365 0.0163 6.0975 0.0135 33/796(4.1%) 21/575 (3.7%) 10/101 (9.9%) 2.54 (1.15 to 5.15) 0.88 (0.49 to1.52) p < 0.05 7514692 Patients Cardiovascular Disease BAT2 hCV- AllHistory of Congestive 9.0538 0.0108 8.3932 0.0038 42/796 (5.3%) 41/575(7.1%) 13/101 (12.9%) 2.65 (1.32 to 5.01) 1.38 (0.88 to 2.15) p <7514692 Patients Heart Failure (AE) 0.005 BCL2A1 hCV- All Nonfatal MI6.0311 0.049 5.7126 0.0168 122/807 61/572 (10.7%) 11/95 (11.6%) 0.74(0.36 to 1.36) 0.67 (0.48 to 0.93) p < 0.05 7509650 Patients(Probable/Definite) (15.1%) BCL2A1 hCV- All Nonfatal MI 7.9668 0.01867.7732 0.0053 117/807 54/572 (9.4%) 11/95 (11.6%) 0.77 (0.38 to 1.43)0.61 (0.43 to 0.86) p < 0.05 7509650 Patients (def & prob) (14.5%) CCL4hCV- All Fatal CHD/Definite 5.9309 0.0149 5.884 0.0153 118/1059 65/411(15.8%) 1.50 (1.08 to 2.07) p < 0.05 12120554 Patients Nonfatal MI(11.1%) CCL4 hCV- All Fatal Coronary 13.1864 0.0003 12.3436 0.000429/1059 (2.7%) 28/411 (6.8%) 2.60 (1.52 to 4.43) p < 12120554 PatientsHeart Disease 0.0005 CCL4 hCV- All Total Mortality 9.1271 0.0025 8.86840.0029 55/1059 (5.2%) 39/411 (9.5%) 1.91 (1.24 to 2.92) p < 12120554Patients 0.005 CCL4 hCV- All Cardiovascular 13.9315 0.0002 13.09440.0003 33/1059 (3.1%) 31/411 (7.5%) 2.54 (1.53 to 4.20) p < 12120554Patients Mortality 0.0005 CCL4 hCV- All Fatal Atherosclerotic 13.93150.0002 13.0944 0.0003 33/1059 (3.1%) 31/411 (7.5%) 2.54 (1.53 to 4.20) p< 12120554 Patients Cardiovascular 0.0005 Disease CCL4 hCV- AllFatal/Nonfatal 4.0079 0.0453 4.0002 0.0455 401/1059 179/411 (43.6%) 1.27(1.00 to 1.59) p < 0.05 12120554 Patients Atherosclerotic (37.9%) CVDisease CD22 hCV- All Coronary Artery 10.9893 0.0041 10.0168 0.001688/930 (9.5%) 50/496 (10.1%) 12/50 (24.0%) 3.02 (1.47 to 5.84) 1.07(0.74 to 1.54) p < 2531086 Patients Bypass Graft 0.005 CD22 hCV- AllCoronary 7.0879 0.0289 6.6326 0.01 175/930 94/496 (19.0%) 17/50 (34.0%)2.22 (1.19 to 4.03) 1.01 (0.76 to 1.33) p < 0.05 2531086 Patients ArteryBypass (18.8%) or Revascularization CD22 hCV- All Hosp. for 7.02070.0299 6.4786 0.0109 162/930 86/496 (17.3%) 16/50 (32.0%) 2.23 (1.17 to4.08) 0.99 (0.74 to 1.32) p < 0.05 2531086 Patients Unstable Angina(17.4%) CD6 hCV- All Congestive 7.2236 0.027 4.9062 0.0268 56/888 (6.3%)47/512 (9.2%) 10/76 (13.2%) 2.25 (1.04 to 4.44) 1.50 (1.00 to 2.25) p <0.05 2553030 Patients Heart Failure CD6 hCV- All Hosp. for Peripheral7.4666 0.0239 6.4999 0.0108 22/888 (2.5%) 14/512 (2.7%) 6/76 (7.9%) 3.37(1.21 to 8.12) 1.11 (0.55 to 2.16) p < 0.05 2553030 Patients ArterialDisease CD6 hCV- All History of Coronary 10.2377 0.006 10.0806 0.0015210/888 161/512 (31.4%) 19/76 (25.0%) 1.08 (0.61 to 1.82) 1.48 (1.16 to1.89) p < 2553030 Patients Artery Bypass Graft (23.6%) 0.005 CD6 hCV-All CARE MI: Non 6.7337 0.0345 5.7915 0.0161 69/888 (7.8%) 51/512(10.0%) 12/75 (16.0%) 2.26 (1.12 to 4.26) 1.31 (0.90 to 1.92) p < 0.052553030 Patients Q-Wave MI CTSH hCV- All Percutaneous 7.1211 0.02845.6616 0.0173 131/1186 26/270 (9.6%) 6/21 (28.6%) 3.22 (1.13 to 8.08)0.86 (0.54 to 1.32) p < 0.05 15882348 Patients Transluminal (11.0%)Coronary Angioplasty CTSS hCV- All Fatal MI 8.2495 0.0162 4.7645 0.02915606 (0.8%) 56/73 (0.7%) 61/96 (3.1%) 3.80 (1.13 to 13.30) 0.90 (0.25 to3.25) p < 0.05 1789791 Patients CTSS hCV- All History of 6.4861 0.0395.2065 0.0225 176/606 229/673 (34.0%) 74/196 (37.8%) 1.48 (1.05 to 2.07)1.26 (0.99 to 1.60) p < 0.05 1789791 Patients Percutaneous (29.0%)Transluminal Coronary Angioplasty CYP4F2 hCV- All Fatal Coronary 9.35850.0093 8.497 0.0036 39/720 (5.4%) 14/629 (2.2%) 4/125 (3.2%) 0.58 (0.17to 1.47) 0.40 (0.21 to 0.72) p < 16179493 Patients Heart Disease 0.005CYP4F2 hCV- All Total Mortality 9.4509 0.0089 6.6827 0.0097 60/720(8.3%) 30/629 (4.8%) 4/125 (3.2%) 0.36 (0.11 to 0.90) 0.55 (0.35 to0.86) p < 0.05 16179493 Patients CYP4F2 hCV- All Congestive 7.55120.0229 4.7724 0.0289 68/720 (9.4%) 39/629 (6.2%) 5/125 (4.0%) 0.40 (0.14to 0.92) 0.63 (0.42 to 0.95) p < 0.05 16179493 Patients Heart FailureCYP4F2 hCV- All Hosp. for 8.1794 0.0167 3.8637 0.0493 138/720 95/629(15.1%) 31/125 (24.8%) 1.39 (0.88 to 2.15) 0.75 (0.56 to 1.00) p < 0.0516179493 Patients Unstable Angina (19.2%) CYP4F2 hCV- All Cardiovascular9.0692 0.0107 8.0291 0.0046 43/720 (6.0%) 17/629 (2.7%) 4/125 (3.2%)0.52 (0.15 to 1.31) 0.44 (0.24 to 0.76) p < 16179493 Patients Mortality0.005 CYP4F2 hCV- All Fatal Atherosclerotic 9.0692 0.0107 8.0291 0.004643720 (6.0%) 17/629 (2.7%) 4/125 (3.2%) 0.52 (0.15 to 1.31) 0.44 (0.24to 0.76) p < 16179493 Patients Cardiovascular 0.005 Disease DDEF1 hCV-All Fatal Coronary 9.6484 0.008 9.0687 0.0026 28/464 (6.0%) 18/727(2.5%) 11/283 (3.9%) 0.63 (0.30 to 1.25) 0.40 (0.21 to 0.72) p < 7686234Patients Heart Disease 0.005 DDEF1 hCV- All History of 7.0086 0.03016.9582 0.0083 172/464 216/727 (29.7%) 91/283 (32.2%) 0.80 (0.59 to 1.10)0.72 (0.56 to 0.92) p < 0.05 7686234 Patients Percutaneous (37.1%)Transluminal Coronary Angioplasty EDN3 hCV- All Congestive 9.3292 0.00948.0301 0.0046 39/435 (9.0%) 63/744 (8.5%) 10/294 (3.4%) 0.36 (0.17 to0.70) 0.94 (0.62 to 1.44) p < 3223182 Patients Heart Failure 0.005FCGR2A hCV- All Fatal Coronary 9.2868 0.0096 7.4361 0.0064 23/363 (6.3%)26/737 (3.5%) 83/77 (2.1%) 0.32 (0.13 to 0.70) 0.54 (0.30 to 0.97) p <0.05 9077561 Patients Heart Disease FCGR2A hCV- All Total Mortality8.9741 0.0113 8.4427 0.0037 33/363 (9.1%) 47/737 (6.4%) 14/377 (3.7%)0.39 (0.20 to 0.72) 0.68 (0.43 to 1.09) p < 9077561 Patients 0.005FCGR2A hCV- All Cardiovascular 10.1866 0.0061 8.823 0.003 25/363 (6.9%)31/737 (4.2%) 83/77 (2.1%) 0.29 (0.12 to 0.63) 0.59 (0.35 to 1.03) p <9077561 Patients Mortality 0.005 FCGR2A hCV- All Fatal Atherosclerotic10.1866 0.0061 8.823 0.003 25/363 (6.9%) 31/737 (4.2%) 8/377 (2.1%) 0.29(0.12 to 0.63) 0.59 (0.35 to 1.03) p < 9077561 Patients Cardiovascular0.005 Disease IL12A hCV- All Coronary Artery 9.5881 0.0083 9.4081 0.002291/1035 (8.8%) 55/381 (14.4%) 4/38 (10.5%) 1.22 (0.36 to 3.15) 1.75(1.22 to 2.49) p < 1403468 Patients Bypass Graft 0.005 IL12A hCV- AllStroke 6.215 0.0447 5.596 0.018 24/458 (5.2%) 30/717 (4.2%) 42/67 (1.5%)0.28 (0.08 to 0.72) 0.79 (0.46 to 1.38) p < 0.05 16053900 Patients IL12AhCV- All Catheterization 9.2674 0.0097 7.7503 0.0054 75/459 (16.3%)77/718 (10.7%) 28/267 (10.5%) 0.60 (0.37 to 0.94) 0.62 (0.44 to 0.87) p< 0.05 16053900 Patients IL12A hCV- All Coronary 9.1727 0.0102 7.82170.0052 109/459 133/718 (18.5%) 40/267 (15.0%) 0.57 (0.38 to 0.84) 0.73(0.55 to 0.97) p < 0.05 16053900 Patients Artery Bypass (23.7%) orRevascularization IL12A hCV- All Total Coronary Heart 5.9977 0.04985.7793 0.0162 171/459 253/718 (35.2%) 76/267 (28.5%) 0.67 (0.48 to 0.93)0.92 (0.72 to 1.17) p < 0.05 16053900 Patients Disease Events (37.3%)IL12A hCV- All Fatal/Nonfatal 9.1922 0.0101 8.9378 0.0028 196/459286/718 (39.8%) 84/267 (31.5%) 0.62 (0.45 to 0.84) 0.89 (0.70 to 1.13) p< 16053900 Patients Atherosclerotic (42.7%) 0.005 CV Disease IL12A hCV-All Any Report 8.2797 0.0159 6.9438 0.0084 25/459 (5.4%) 30/718 (4.2%)3/267 (1.1%) 0.20 (0.05 to 0.57) 0.76 (0.44 to 1.31) p < 0.05 16053900Patients of Stroke Prior to or During CARE IL12A hCV- All 1st StrokeOccurred 6.7045 0.035 5.7565 0.0164 22/459 (4.8%) 26/718 (3.6%) 3/267(1.1%) 0.23 (0.05 to 0.66) 0.75 (0.42 to 1.34) p < 0.05 16053900Patients During CARE IL1RL1 hCV- All Definite 11.894 0.0026 5.77080.0163 53/564 (9.4%) 52/679 (7.7%) 36/235 (15.3%) 1.74 (1.10 to 2.74)0.80 (0.54 to 1.19) p < 0.05 25607108 Patients Nonfatal MI IL1RL1 hCV-All Fatal MI 7.5954 0.0224 5.9238 0.0149 2/564 (0.4%) 8/679 (1.2%) 6/235(2.6%) 7.36 (1.68 to 50.49) 3.35 (0.84 to p < 0.05 25607108 Patients22.26) IL1RL1 hCV- All Fatal CHD/Definite 8.5336 0.014 6.7904 0.009264/564 (11.3%) 78/679 (11.5%) 43/235 (18.3%) 1.75 (1.14 to 2.66) 1.01(0.71 to 1.44) p < 0.05 25607108 Patients Nonfatal MI IL1RL1 hCV- AllFatal Coronary 6.188 0.0453 5.8909 0.0152 13/564 (2.3%) 34/679 (5.0%)10/235 (4.3%) 1.88 (0.79 to 4.34) 2.23 (1.20 to 4.43) p < 0.05 25607108Patients Heart Disease IL1RL1 hCV- All Total Mortality 7.1672 0.02786.9439 0.0084 24/564 (4.3%) 54/679 (8.0%) 16/235 (6.8%) 1.64 (0.84 to3.13) 1.94 (1.20 to 3.24) p < 0.05 25607108 Patients IL1RL1 hCV- AllHosp. for 9.0023 0.0111 8.4372 0.0037 111/564 127/679 (18.7%) 26/235(11.1%) 0.51 (0.32 to 0.79) 0.94 (0.71 to 1.25) p < 25607108 PatientsUnstable Angina (19.7%) 0.005 IL1RL1 hCV- All Cardiovascular 7.07790.029 6.7239 0.0095 15/564 (2.7%) 39/679 (5.7%) 10/235 (4.3%) 1.63 (0.70to 3.64) 2.23 (1.24 to 4.21) p < 0.05 25607108 Patients Mortality IL1RL1hCV- All Fatal Atherosclerotic 7.0779 0.029 6.7239 0.0095 15/564 (2.7%)39/679 (5.7%) 10/235 (4.3%) 1.63 (0.70 to 3.64) 2.23 (1.24 to 4.21) p <0.05 25607108 Patients Cardiovascular Disease KIAA- hCV- All Stroke6.2709 0.0435 3.9375 0.0472 35/669 (5.2%) 21/620 (3.4%) 2/157 (1.3%)0.23 (0.04 to 0.78) 0.64 (0.36 to 1.09) p < 0.05 0329 1662671 PatientsKIAA- hCV- All Any Report of Stroke 6.5108 0.0386 4.0999 0.0429 36/670(5.4%) 19/620 (3.1%) 3/158 (1.9%) 0.34 (0.08 to 0.96) 0.56 (0.31 to0.97) p < 0.05 0329 1662671 Patients During CARE KIAA- hCV- All MI(Fatal/Nonfatal) 9.5857 0.002 9.1277 0.0025 180/1365 20/78 (25.6%) 2.27(1.30 to 3.80) p < 0329 25751017 Patients (13.2%) 0.005 KIAA- hCV- AllNonfatal MI 9.3425 0.0022 8.8902 0.0029 169/1365 19/78 (24.4%) 2.28(1.30 to 3.85) p < 0329 25751017 Patients (Probable/Definite) (12.4%)0.005 KIAA- hCV- All Fatal CHD/Definite 6.6912 0.0097 6.4342 0.0112162/1365 17/78 (21.8%) 2.07 (1.15 to 3.55) p < 0.05 0329 25751017Patients Nonfatal MI (11.9%) KIAA- hCV- All Nonfatal MI 7.0931 0.00776.8051 0.0091 159/1365 17/78 (21.8%) 2.11 (1.17 to 3.63) p < 0.05 032925751017 Patients (def & prob) (11.6%) KIAA- hCV- All Fatal/Nonfatal9.8958 0.0017 9.4086 0.0022 178/1365 20/78 (25.6%) 2.30 (1.32 to 3.85) p< 0329 25751017 Patients MI (def & prob) (13.0%) 0.005 KIAA- hCV- AllHistory of 5.8485 0.0156 5.6948 0.017 266/1365 24/78 (30.8%) 1.84 (1.10to 2.99) p < 0.05 0329 25751017 Patients Angina Pectoris (19.5%) KIAA-hCV- All History of Congestive 14.6298 0.0001 13.1769 0.0003 79/1365(5.8%) 13/78 (16.7%) 3.26 (1.66 to 5.98) p < 0329 25751017 PatientsHeart Failure (AE) 0.0005 KIAA- hCV- All More Than 9.2578 0.0023 8.84440.0029 195/1365 21/78 (26.9%) 2.21 (1.28 to 3.67) p < 0329 25751017Patients 1 Prior MI (14.3%) 0.005 KLK1 hCV- All Congestive 8.9138 0.01167.7742 0.0053 44/660 (6.7%) 47/664 (7.1%) 21/155 (13.5%) 2.19 (1.24 to3.77) 1.07 (0.70 to 1.64) p < 0.05 8705506 Patients Heart Failure KLK1hCV- All More Than 11.8625 0.0027 7.535 0.0061 97/660 (14.7%) 86/664(13.0%) 37/155 (23.9%) 1.82 (1.18 to 2.77) 0.86 (0.63 to 1.18) p < 0.058705506 Patients 1 Prior MI KLK14 hCV- All MI (Fatal/Nonfatal) 11.95950.0025 11.623 0.0007 81/685 (11.8%) 89/629 (14.1%) 35/156 (22.4%) 2.16(1.37 to 3.33) 1.23 (0.89 to 1.70) p < 16044337 Patients 0.005 KLK14hCV- All Nonfatal MI 10.3731 0.0056 9.8772 0.0017 79/685 (11.5%) 81/629(12.9%) 33/156 (21.2%) 2.06 (1.30 to 3.20) 1.13 (0.81 to 1.58) p <16044337 Patients (Probable/Definite) 0.005 KLK14 hCV- All DefiniteNonfatal MI 8.8701 0.0119 8.2722 0.004 57/685 (8.3%) 58/629 (9.2%)25/156 (16.0%) 2.10 (1.25 to 3.45) 1.12 (0.76 to 1.64) p < 16044337Patients 0.005 KLK14 hCV- All Fatal MI 11.2134 0.0037 8.3119 0.00392/685 (0.3%) 9/629 (1.4%) 5/156 (3.2%) 11.31 (2.41 to 4.96 (1.27 to p <16044337 Patients 79.44) 32.60) 0.005 KLK14 hCV- All Coronary Artery6.4727 0.0393 6.2691 0.0123 57/685 (8.3%) 79/629 (12.6%) 15/156 (9.6%)1.17 (0.62 to 2.08) 1.58 (1.11 to 2.27) p < 0.05 16044337 PatientsBypass Graft KLK14 hCV- All Fatal CHD/Definite 11.2734 0.0036 10.89860.001 73/685 (10.7%) 79/629 (12.6%) 32/156 (20.5%) 2.16 (1.35 to 3.40)1.20 (0.86 to 1.69) p < 16044337 Patients Nonfatal MI 0.005 KLK14 hCV-All Nonfatal MI 11.0705 0.0039 10.1263 0.0015 75/685 (10.9%) 74/629(11.8%) 32/156 (20.5%) 2.10 (1.32 to 3.29) 1.08 (0.77 to 1.53) p <16044337 Patients (def & prob) 0.005 KLK14 hCV- All Fatal/Nonfatal12.3831 0.002 12.0168 0.0005 80/685 (11.7%) 88/629 (14.0%) 35/156(22.4%) 2.19 (1.39 to 3.38) 1.23 (0.89 to 1.70) p < 16044337 Patients MI(def & prob) 0.005 KLK14 hCV- All History of Diabetes 7.2874 0.02627.1207 0.0076 91/685 (13.3%) 93/629 (14.8%) 34/156 (21.8%) 1.82 (1.16 to2.80) 1.13 (0.83 to 1.55) p < 0.05 16044337 Patients KLK14 hCV- AllFamily History 7.7839 0.0204 7.6659 0.0056 294/685 258/629 (41.0%)48/156 (30.8%) 0.59 (0.40 to 0.85) 0.92 (0.74 to 1.15) p < 0.05 16044337Patients of CV Disease (42.9%) LAMA2 hCV- All Hosp. for 6.7501 0.03425.5114 0.0189 134/769 98/588 (16.7%) 32/121 (26.4%) 1.70 (1.08 to 2.64)0.95 (0.71 to 1.26) p < 0.05 1819516 Patients Unstable Angina (17.4%)MARK3 hCV- All MI (Fatal/Nonfatal) 8.101 0.0174 7.1106 0.0077 62/573(10.8%) 104/646 (16.1%) 37/228 (16.2%) 1.60 (1.02 to 2.47) 1.58 (1.13 to2.22) p < 0.05 25926178 Patients MARK3 hCV- All Nonfatal MI 8.81320.0122 7.3651 0.0067 57/573 (9.9%) 98/646 (15.2%) 36/228 (15.8%) 1.70(1.08 to 2.65) 1.62 (1.15 to 2.30) p < 0.05 25926178 Patients(Probable/Definite) MARK3 hCV- All Definite 6.5601 0.0376 6.4606 0.01141/573 (7.2%) 74/646 (11.5%) 22/228 (9.6%) 1.39 (0.79 to 2.36) 1.68(1.13 to 2.52) p < 0.05 25926178 Patients Nonfatal MI MARK3 hCV- AllNonfatal MI 9.5045 0.0086 8.4948 0.0036 52/573 (9.1%) 94/646 (14.6%)33/228 (14.5%) 1.70 (1.06 to 2.69) 1.71 (1.20 to 2.46) p < 25926178Patients (def & prob) 0.005 MARK3 hCV- All Fatal/Nonfatal MI 8.36330.0153 7.2345 0.0072 61/573 (10.6%) 103/646 (15.9%) 37/228 (16.2%) 1.63(1.04 to 2.52) 1.59 (1.14 to 2.24) p < 0.05 25926178 Patients (def &prob) MARK3 hCV- All MI (Fatal/Nonfatal) 10.7762 0.001 10.5972 0.001158/566 (10.2%) 144/879 (16.4%) 1.72 (1.25 to 2.39) p < 25926771 Patients0.005 MARK3 hCV- All Nonfatal MI 12.7866 0.0003 12.5077 0.0004 52/566(9.2%) 138/879 (15.7%) 1.84 (1.32 to 2.60) p < 25926771 Patients(Probable/Definite) 0.0005 MARK3 hCV- All Definite 9.3959 0.0022 9.17210.0025 37/566 (6.5%) 100/879 (11.4%) 1.84 (1.25 to 2.75) p < 25926771Patients Nonfatal MI 0.005 MARK3 hCV- All Fatal CHD/Definite 5.88250.0153 5.8181 0.0159 56/566 (9.9%) 125/879 (14.2%) 1.51 (1.09 to 2.12) p< 0.05 25926771 Patients Nonfatal MI MARK3 hCV- All Nonfatal MI 12.6880.0004 12.3884 0.0004 48/566 (8.5%) 130/879 (14.8%) 1.87 (1.33 to 2.68)p < 25926771 Patients (def & prob) 0.0005 MARK3 hCV- All Fatal/Nonfatal11.0905 0.0009 10.8977 0.001 57/566 (10.1%) 143/879 (16.3%) 1.74 (1.26to 2.42) p < 25926771 Patients MI (def & prob) 0.005 MARK3 hCV- All 1stStroke Occurred 4.1518 0.0416 4.0187 0.045 13/566 (2.3%) 38/879 (4.3%)1.92 (1.04 to 3.78) p < 0.05 25926771 Patients During CARE MMP27 hCV-All Percutaneous 6.0292 0.0491 5.8699 0.0154 59/668 (8.8%) 84/645(13.0%) 19/160 (11.9%) 1.39 (0.79 to 2.37) 1.55 (1.09 to 2.21) p < 0.057492597 Patients Transluminal Coronary Angioplasty MMP27 hCV- AllPercutaneous 8.7778 0.0124 8.6086 0.0033 36/449 (8.0%) 81/715 (11.3%)46/310 (14.8%) 2.00 (1.26 to 3.19) 1.47 (0.98 to 2.23) p < 7492601Patients Transluminal 0.005 Coronary Angioplasty MMP27 hCV- AllCatheterization 8.8894 0.0117 7.5393 0.006 47/449 (10.5%) 84/715 (11.7%)54/310 (17.4%) 1.80 (1.18 to 2.76) 1.14 (0.78 to 1.67) p < 0.05 7492601Patients MMP27 hCV- All Total Mortality 6.5936 0.037 5.9846 0.014438/449 (8.5%) 44/715 (6.2%) 12/310 (3.9%) 0.44 (0.21 to 0.82) 0.71 (0.45to 1.12) p < 0.05 7492601 Patients NUDT6 hCV- All History of 9.71720.0078 8.9124 0.0028 317/785 254/571 (44.5%) 65/118 (55.1%) 1.81 (1.23to 2.68) 1.18 (0.95 to 1.47) p < 25956925 Patients Hypertension (40.4%)0.005 PLAT hCV- All Coronary 4.9189 0.0266 4.5384 0.0331 280/1407 5/60(8.3%) 0.37 (0.13 to 0.84) p < 0.05 12108245 Patients Artery Bypass(19.9%) or Revascularization PON2 hCV- All CARE MI: 6.1557 0.0461 4.95570.026 570/872 322/524 (61.5%) 44/83 (53.0%) 0.60 (0.38 to 0.94) 0.84(0.67 to 1.06) p < 0.05 8952817 Patients Q-Wave MI (65.4%) PPOX hCV- AllPercutaneous 9.1866 0.0101 4.8253 0.028 129/1264 28/178 (15.7%) 2/5(40.0%) 5.87 (0.77 to 35.70) 1.64 (1.04 to 2.52) p < 0.05 25922816Patients Transluminal (10.2%) Coronary Angioplasty PPOX hCV- AllCoronary 12.759 0.0017 7.4351 0.0064 231/1264 48/178 (27.0%) 3/5 (60.0%)6.70 (1.11 to 51.14) 1.65 (1.14 to 2.35) p < 0.05 25922816 PatientsArtery Bypass (18.3%) or Revascularization PPOX hCV- All Hosp. for7.7482 0.0208 5.5017 0.019 577/1264 98/178 (55.1%) 4/5 (80.0%) 4.76(0.70 to 93.24) 1.46 (1.06 to 2.00) p < 0.05 25922816 PatientsCardiovascular (45.6%) Disease PPOX hCV- All Hosp. for 7.8955 0.01937.7455 0.0054 211/1264 45/178 (25.3%) 1/5 (20.0%) 1.25 (0.06 to 8.48)1.69 (1.16 to 2.43) p < 0.05 25922816 Patients Unstable Angina (16.7%)PPOX hCV- All Total Coronary Heart 9.8483 0.0073 8.3457 0.0039 421/126479/178 (44.4%) 3/5 (60.0%) 3.00 (0.50 to 22.87) 1.60 (1.16 to 2.19) p <25922816 Patients Disease Events (33.3%) 0.005 PPOX hCV- All TotalCardiovascular 8.7618 0.0125 6.6786 0.0098 593/1264 102/178 (57.3%) 4/5(80.0%) 4.53 (0.67 to 88.61) 1.52 (1.11 to 2.09) p < 0.05 25922816Patients Disease Events (46.9%) PPOX hCV- All Fatal/Nonfatal 10.57830.005 7.0358 0.008 479/1264 86/178 (48.3%) 4/5 (80.0%) 6.56 (0.97 to1.53 (1.12 to 2.10) p < 0.05 25922816 Patients Atherosclerotic (37.9%)128.35) CV Disease PRG1 hCV- All Fatal MI 11.4732 0.0032 6.2891 0.012111/1007 (1.1%) 24/15 (0.5%) 3/54 (5.6%) 5.33 (1.18 to 17.69) 0.44 (0.07to 1.64) p < 0.05 1842400 Patients PRG1 hCV- All Fatal Coronary 8.82390.0121 7.7888 0.0053 33/1007 (3.3%) 18/415 (4.3%) 6/54 (11.1%) 3.69(1.34 to 8.66) 1.34 (0.73 to 2.38) p < 0.05 1842400 Patients HeartDisease PRG1 hCV- All Fatal/Nonfatal 6.2693 0.0435 3.8612 0.0494143/1007 49415 (11.8%) 13/54 (24.1%) 1.92 (0.97 to 3.57) 0.81 (0.57 to1.14) p < 0.05 1842400 Patients MI (def & prob) (14.2%) PRG1 hCV- AllCardiovascular 6.555 0.0377 5.9856 0.0144 39/1007 (3.9%) 19/415 (4.6%)6/54 (11.1%) 3.10 (1.14 to 7.19) 1.19 (0.67 to 2.06) p < 0.05 1842400Patients Mortality PRG1 hCV- All Fatal Atherosclerotic 6.555 0.03775.9856 0.0144 39/1007 (3.9%) 19/415 (4.6%) 6/54 (11.1%) 3.10 (1.14 to7.19) 1.19 (0.67 to 2.06) p < 0.05 1842400 Patients CardiovascularDisease PTGIS hCV- All Fatal/Nonfatal 7.804 0.0202 6.0104 0.0142 51/558(9.1%) 37/674 (5.5%) 12/238 (5.0%) 0.53 (0.26 to 0.98) 0.58 (0.37 to0.89) p < 0.05 2782570 Patients Cerebrovascular Disease PTGIS hCV- AllAny Report 7.068 0.0292 6.1437 0.0132 46/558 (8.2%) 32/674 (4.7%) 12/238(5.0%) 0.59 (0.29 to 1.10) 0.55 (0.35 to 0.88) p < 0.05 2782570 Patientsof Stroke Prior to or During CARE PTPN21 hCV- All Stroke 12.2467 0.002211.1265 0.0009 14/615 (2.3%) 31/671 (4.6%) 13/162 (8.0%) 3.75 (1.70 to8.18) 2.08 (1.12 to 4.07) p < 16182835 Patients 0.005 PTPN21 hCV- AllFatal/Nonfatal 6.7201 0.0347 5.5243 0.0188 30/615 (4.9%) 51/673 (7.6%)16/162 (9.9%) 2.14 (1.11 to 3.97) 1.60 (1.01 to 2.57) p < 0.05 16182835Patients Cerebrovascular Disease PTPN21 hCV- All Any Report 11.82490.0027 10.3066 0.0013 24/615 (3.9%) 48/673 (7.1%) 17/162 (10.5%) 2.89(1.49 to 5.49) 1.89 (1.16 to 3.17) p < 16182835 Patients of Stroke Prior0.005 to or During CARE PTPN21 hCV- All Any Report of Stroke 12.23550.0022 11.1265 0.0009 14/615 (2.3%) 31/673 (4.6%) 13/162 (8.0%) 3.75(1.70 to 8.18) 2.07 (1.11 to 4.05) p < 16182835 Patients During CARE0.005 PTPN21 hCV- All 1st Stroke Occurred 12.1541 0.0023 11.0615 0.000912/615 (2.0%) 27/673 (4.0%) 12/162 (7.4%) 4.02 (1.75 to 9.22) 2.10 (1.08to 4.34) p < 16182835 Patients During CARE 0.005 PTPN21 hCV- All Stroke9.372 0.0092 8.6113 0.0033 16/620 (2.6%) 31/671 (4.6%) 12/155 (7.7%)3.17 (1.44 to 6.81) 1.83 (1.00 to 3.46) p < 25942539 Patients 0.005PTPN21 hCV- All Any Report 9.804 0.0074 8.5121 0.0035 26/620 (4.2%)48/673 (7.1%) 16/155 (10.3%) 2.63 (1.35 to 4.99) 1.75 (1.08 to 2.90) p <25942539 Patients of Stroke Prior 0.005 hCV- to or During CARE PTPN2125942539 All Any Report of Stroke 9.3606 0.0093 8.6114 0.0033 16/620(2.6%) 31/673 (4.6%) 12/155 (7.7%) 3.17 (1.44 to 6.81) 1.82 (1.00 to3.45) p < hCV- Patients During CARE 0.005 PTPN21 25942539 All 1st StrokeOccurred 9.0284 0.011 8.367 0.0038 14/620 (2.3%) 27/673 (4.0%) 11/155(7.1%) 3.31 (1.44 to 7.42) 1.81 (0.95 to 3.58) p < hCV- Patients DuringCARE 0.005 PTPRJ hCV- All Stroke 8.0699 0.0177 4.9043 0.0268 15/455(3.3%) 23/709 (3.2%) 21/307 (6.8%) 2.15 (1.10 to 4.32) 0.98 (0.51 to1.94) p < 0.05 25943544 Patients PTPRJ hCV- All Any Report of Stroke12.2226 0.0022 6.4092 0.0114 15/455 (3.3%) 21/710 (3.0%) 23/308 (7.5%)2.37 (1.23 to 4.71) 0.89 (0.46 to 1.78) p < 0.05 25943544 PatientsDuring CARE SCARF1 hCV- All Percutaneous 6.3674 0.0414 5.0636 0.024451/520 (9.8%) 70/694 (10.1%) 40/261 (15.3%) 1.66 (1.06 to 2.59) 1.03(0.71 to 1.51) p < 0.05 12114319 Patients Transluminal CoronaryAngioplasty SER- hCV- All Coronary Artery 6.8645 0.0323 6.6037 0.010286/705 (12.2%) 43/413 (10.4%) 18/277 (6.5%) 0.50 (0.29 to 0.83) 0.84(0.56 to 1.23) p < 0.05 PINA1 25640505 Patients Bypass Graft SER- hCV-All Any Report 6.1297 0.0467 4.7864 0.0287 48/705 (6.8%) 15/413 (3.6%)21/277 (7.6%) 1.12 (0.65 to 1.89) 0.52 (0.28 to 0.91) p < 0.05 PINA125640505 Patients of Stroke Prior to or During CARE SER- hCV- AllFatal/Nonfatal 10.0396 0.0066 3.9528 0.0468 53/732 (7.2%) 30/603 (5.0%)17/138 (12.3%) 1.80 (0.98 to 3.15) 0.67 (0.42 to 1.06) p < 0.05 PINB616190893 Patients Cerebrovascular Disease SER- hCV- All Fatal/Nonfatal7.2903 0.0261 5.6856 0.0171 286/732 227/603 (37.6%) 69/138 (50.0%) 1.56(1.08 to 2.25) 0.94 (0.75 to 1.18) p < 0.05 PINB6 16190893 PatientsAtherosclerotic (39.1%) CV Disease SER- hCV- All MI (Fatal/Nonfatal)9.4616 0.0088 6.3892 0.0115 91/515 (17.7%) 85/683 (12.4%) 30/277 (10.8%)0.57 (0.36 to 0.87) 0.66 (0.48 to 0.91) p < 0.05 PINB8 3023236 PatientsSER- hCV- All Nonfatal MI 8.0517 0.0178 5.6357 0.0176 85/515 (16.5%)80/683 (11.7%) 29/277 (10.5%) 0.59 (0.37 to 0.92) 0.67 (0.48 to 0.93) p< 0.05 PINB8 3023236 Patients (Probable/Definite) SER- hCV- All Nonfatal7.7449 0.0208 5.3563 0.0206 80/515 (15.5%) 75/683 (11.0%) 27/277 (9.7%)0.59 (0.36 to 0.92) 0.67 (0.48 to 0.94) p < 0.05 PINB8 3023236 PatientsMI (def & prob) SER- hCV- All Fatal/Nonfatal 8.3387 0.0155 5.772 0.016389/515 (17.3%) 85/683 (12.4%) 30/277 (10.8%) 0.58 (0.37 to 0.90) 0.68(0.48 to 0.94) p < 0.05 PINB8 3023236 Patients MI (def & prob) SER- hCV-All Fatal/Nonfatal 6.6908 0.0352 4.0053 0.0454 214/515 245/683 (35.9%)121/277 (43.7%) 1.09 (0.81 to 1.47) 0.79 (0.62 to 1.00) p < 0.05 PINB83023236 Patients Atherosclerotic (41.6%) CV Disease SN hCV- AllPercutaneous 7.1386 0.0282 5.7749 0.0163 57/396 (14.4%) 76/745 (10.2%)29/337 (8.6%) 0.56 (0.35 to 0.89) 0.68 (0.47 to 0.98) p < 0.05 25623265Patients Transluminal Coronary Angioplasty SN hCV- All Catherization14.4805 0.0007 12.4057 0.0004 71/396 (17.9%) 78/745 (10.5%) 36/337(10.7%) 0.55 (0.35 to 0.84) 0.54 (0.38 to 0.76) p < 25623265 Patients0.0005 SN hCV- All Coronary Artery 11.6208 0.003 9.3889 0.0022 99/396(25.0%) 135/745 (18.1%) 53/337 (15.7%) 0.56 (0.38 to 0.81) 0.66 (0.50 to0.89) p < 25623265 Patients Bypass 0.005 or Revascularization SN hCV-All Hosp. for 6.7526 0.0342 5.2835 0.0215 201/396 325/745 (43.6%)168/337 (49.9%) 0.96 (0.72 to 1.29) 0.75 (0.59 to 0.96) p < 0.0525623265 Patients Cardiovascular (50.8%) Disease SN hCV- All Hosp. for7.1878 0.0275 6.7216 0.0095 86/396 (21.7%) 129/745 (17.3%) 48/337(14.2%) 0.60 (0.40 to 0.88) 0.75 (0.56 to 1.03) p < 0.05 25623265Patients Unstable Angina SN hCV- All History of Stroke 8.5497 0.01396.7929 0.0092 3/396 (0.8%) 27/745 (3.6%) 8/337 (2.4%) 3.19 (0.91 to14.63) 4.93 (1.73 to 20.71) p < 0.05 25623265 Patients SN hCV- AllCoronary Artery 6.3825 0.0411 5.345 0.0208 69/539 (12.8%) 62/710 (8.7%)19/224 (8.5%) 0.63 (0.36 to 1.06) 0.65 (0.45 to 0.94) p < 0.05 2992252Patients Bypass Graft SN hCV- All Catherization 9.4523 0.0089 7.39880.0065 86/539 (16.0%) 76/710 (10.7%) 22/224 (9.8%) 0.57 (0.34 to 0.93)0.63 (0.45 to 0.88) p < 0.05 2992252 Patients SN hCV- All Coronary9.8313 0.0073 7.0387 0.008 126/539 126/710 (17.7%) 33/224 (14.7%) 0.57(0.37 to 0.85) 0.71 (0.54 to 0.93) p < 0.05 2992252 Patients ArteryBypass (23.4%) or Revascularization SN hCV- All Hosp. for 6.0158 0.04945.3573 0.0206 111/539 122/710 (17.2%) 30/224 (13.4%) 0.60 (0.38 to 0.91)0.80 (0.60 to 1.07) p < 0.05 2992252 Patients Unstable Angina (20.6%)SOAT2 hCV- All Coronary Artery 6.397 0.0408 5.9871 0.0144 98/1007 (9.7%)45/430 (10.5%) 9/41 (22.0%) 2.61 (1.14 to 5.41) 1.08 (0.74 to 1.56) p <0.05 15962586 Patients Bypass Graft SOAT2 hCV- All Total Mortality6.4718 0.0393 5.1538 0.0232 75/1007 (7.4%) 18/430 (4.2%) 1/41 (2.4%)0.31 (0.02 to 1.46) 0.54 (0.31 to 0.90) p < 0.05 15962586 PatientsSPARCL1 hCV- All MI (Fatal/Nonfatal) 10.1729 0.0062 6.3913 0.0115 77577(13.3%) 82/675 (12.1%) 45/218 (20.6%) 1.69 (1.12 to 2.53) 0.90 (0.64 to1.25) p < 0.05 8827241 Patients SPARCL1 hCV- All Nonfatal MI 7.49880.0235 5.4507 0.0196 71/577 (12.3%) 80/675 (11.9%) 41/218 (18.8%) 1.65(1.08 to 2.50) 0.96 (0.68 to 1.35) p < 0.05 8827241 Patients(Probable/Definite) SPARCL1 hCV- All Nonfatal MI 9.0581 0.0108 6.06620.0138 67/577 (11.6%) 73/675 (10.8%) 40/218 (18.3%) 1.71 (1.11 to 2.61)0.92 (0.65 to 1.31) p < 0.05 8827241 Patients (def & prob) SPARCL1 hCV-All Fatal/Nonfatal MI 9.436 0.0089 5.6592 0.0174 77/577 (13.3%) 81/675(12.0%) 44/218 (20.2%) 1.64 (1.09 to 2.46) 0.89 (0.63 to 1.24) p < 0.058827241 Patients (def & prob) SPARCL1 hCV- All Total Coronary Heart8.9684 0.0113 8.2806 0.004 188/577 228/675 (33.8%) 95/218 (43.6%) 1.60(1.16 to 2.20) 1.06 (0.83 to 1.34) p < 8827241 Patients Disease Events(32.6%) 0.005 SPARCL1 hCV- All Total Cardiovascular 5.9975 0.0498 4.52950.0333 274/577 315/675 (46.7%) 122/218 (56.0%) 1.41 (1.03 to 1.93) 0.97(0.77 to 1.21) p < 0.05 8827241 Patients Disease Events (47.5%) SPARCL1hCV- All More Than 7.4735 0.0238 5.1023 0.0239 96/577 (16.6%) 82675(12.1%) 40/218 (18.3%) 1.13 (0.74 to 1.68) 0.69 (0.50 to 0.95) p < 0.058827241 Patients 1 Prior MI SPATA7 hCV- All Fatal/Nonfatal 7.2724 0.02645.2324 0.0222 43/465 (9.2%) 44/725 (6.1%) 11/250 (4.4%) 0.45 (0.22 to0.86) 0.63 (0.41 to 0.98) p < 0.05 2485037 Patients CerebrovascularDisease SPATA7 hCV- All History of 6.9271 0.0313 5.2953 0.0214 171/465220/725 (30.3%) 72/250 (28.8%) 0.70 (0.50 to 0.97) 0.75 (0.59 to 0.96) p< 0.05 2485037 Patients Percutaneous (36.8%) Transluminal CoronaryAngioplasty SPATA7 hCV- All Any Report 9.9552 0.0069 7.3899 0.006641/465 (8.8%) 40/725 (5.5%) 8/250 (3.2%) 0.34 (0.15 to 0.70) 0.60 (0.38to 0.95) p < 0.05 2485037 Patients of Stroke Prior to or During CARESPATA7 hCV- All Any Report of 9.8656 0.0072 6.823 0.009 29/465 (6.2%)26/725 (3.6%) 4/250 (1.6%) 0.24 (0.07 to 0.63) 0.56 (0.32 to 0.96) p <0.05 2485037 Patients Stroke During CARE SPATA7 hCV- All 1st StrokeOccurred 7.4687 0.0239 5.2807 0.0216 25/465 (5.4%) 23/725 (3.2%) 4/250(1.6%) 0.29 (0.08 to 0.75) 0.58 (0.32 to 1.03) p < 0.05 2485037 PatientsDuring CARE TGFB1 hCV- All Total Mortality 7.5472 0.023 6.5204 0.010722/538 (4.1%) 52/678 (7.7%) 20254 (7.9%) 2.00 (1.07 to 3.75) 1.95 (1.18to 3.31) p < 0.05 22272997 Patients TGFB1 hCV- All Cardiovascular 7.80620.0202 6.1764 0.0129 13/538 (2.4%) 36/678 (5.3%) 15254 (5.9%) 2.53 (1.19to 5.49) 2.26 (1.22 to 4.47) p < 0.05 22272997 Patients Mortality TGFB1hCV- All Fatal Atherosclerotic 7.8062 0.0202 6.1764 0.0129 13/538 (2.4%)36/678 (5.3%) 15254 (5.9%) 2.53 (1.19 to 5.49) 2.26 (1.22 to 4.47) p <0.05 22272997 Patients Cardiovascular Disease TGFB1 hCV- All More Than8.2241 0.0164 7.272 0.007 63538 (11.7%) 109/678 (16.1%) 48/254 (18.9%)1.76 (1.16 to 2.64) 1.44 (1.04 to 2.02) p < 0.05 22272997 Patients 1Prior MI TGOLN2 hCV- All Percutaneous 12.3407 0.0021 10.0079 0.001652/548 (9.5%) 68/676 (10.1%) 43/246 (17.5%) 2.02 (1.30 to 3.12) 1.07(0.73 to 1.57) p < 25615626 Patients Transluminal 0.005 CoronaryAngioplasty TGOLN2 hCV- All Coronary Artery 8.9099 0.0116 8.6407 0.003393/548 (17.0%) 130/676 (19.2%) 64/246 (26.0%) 1.72 (1.20 to 2.47) 1.16(0.87 to 1.57) p < 25615626 Patients Bypass 0.005 or RevascularizationTGOLN2 hCV- All Hosp. for 7.1053 0.0286 5.8082 0.016 80/548 (14.6%)130/676 (19.2%) 53/246 (21.5%) 1.61 (1.09 to 2.36) 1.39 (1.03 to 1.89) p< 0.05 25615626 Patients Unstable Angina TGOLN2 hCV- All History of7.2218 0.027 6.5235 0.0106 99/548 (18.1%) 129/676 (19.1%) 64/246 (26.0%)1.60 (1.11 to 2.28) 1.07 (0.80 to 1.43) p < 0.05 25615626 PatientsAngina Pectoris TGOLN2 hCV- All History of Stroke 9.4434 0.0089 5.150.0232 22/548 (4.0%) 15/676 (2.2%) 1/246 (0.4%) 0.10 (0.01 to 0.47) 0.54(0.27 to 1.05) p < 0.05 25615626 Patients TGOLN2 hCV- All Any Report7.8803 0.0194 5.2621 0.0218 45/548 (8.2%) 35/676 (5.2%) 9/246 (3.7%)0.42 (0.19 to 0.84) 0.61 (0.38 to 0.96) p < 0.05 25615626 Patients ofStroke Prior to or During CARE TLR6 hCV- All Catheterization 5.16130.0231 4.9743 0.0257 172/1407 14/64 (21.9%) 2.01 (1.05 to 3.62) p < 0.0525615376 Patients (12.2%) TLR6 hCV- All CARE MI: 5.1695 0.023 4.99740.0254 880/1407 49/64 (76.6%) 1.96 (1.11 to 3.64) p < 0.05 25615376Patients Q-Wave MI (62.5%) TNFRSF- hCV- All Any Report of Stroke 10.89670.0043 9.2159 0.0024 74/53 (1.5%) 34/712 (4.8%) 18/309 (5.8%) 3.94 (1.69to 10.24) 3.20 (1.49 to 7.92) p < 10A 11852251 Patients During CARE0.005 TNFRSF- hCV- All 1st Stroke Occurred 15.0864 0.0005 12.0652 0.000544/53 (0.9%) 30/712 (4.2%) 18/309 (5.8%) 6.94 (2.56 to 24.21) 4.94 (1.93to 16.71) p < 10A 11852251 Patients During CARE 0.005 TNFRSF- hCV- AllPercutaneous 11.2081 0.0037 10.0042 0.0016 106/1055 45/378 (11.9%) 11/42(26.2%) 3.18 (1.49 to 6.33) 1.21 (0.83 to 1.74) p < 10A 15852235Patients Transluminal (10.0%) 0.005 Coronary Angioplasty TNFRSF- hCV-All Total Coronary Heart 6.479 0.0392 6.0116 0.0142 355/1055 135/378(35.7%) 22/42 (52.4%) 2.17 (1.17 to 4.06) 1.10 (0.86 to 1.40) p < 0.0510A 15852235 Patients Disease Events (33.6%) TNFRSF- hCV- AllCardiovascular 6.169 0.0458 5.3279 0.021 43/1055 (4.1%) 15/378 (4.0%)5/42 (11.9%) 3.18 (1.05 to 7.84) 0.97 (0.52 to 1.73) p < 0.05 10A15852235 Patients Mortality TNFRSF- hCV- All Fatal Atherosclerotic 6.1690.0458 5.3279 0.021 43/1055 (4.1%) 15/378 (4.0%) 5/42 (11.9%) 3.18 (1.05to 7.84) 0.97 (0.52 to 1.73) p < 0.05 10A 15852235 PatientsCardiovascular Disease TNFRSF- hCV- All History of 8.8876 0.0118 8.79220.003 190/1055 95/378 (25.1%) 8/42 (19.0%) 1.07 (0.46 to 2.24) 1.53(1.15 to 2.02) p < 10A 15852235 Patients Angina Pectoris (18.0%) 0.005TNFRSF- hCV- All Family History of 10.6888 0.0048 10.3253 0.0013405/1055 181/378 (47.9%) 19/42 (45.2%) 1.33 (0.71 to 2.46) 1.47 (1.16 to1.87) p < 10A 15852235 Patients CV Disease (38.4%) 0.005 VEGF hCV- AllFatal CHD/Definite 9.3214 0.0095 8.6915 0.0032 103/673 60/613 (9.8%)18/164 (11.0%) 0.68 (0.39 to 1.14) 0.60 (0.43 to 0.84) p < 1647371Patients Nonfatal MI (15.3%) 0.005 VEGF hCV- All Fatal Coronary 8.28730.0159 7.3006 0.0069 37/673 (5.5%) 15/613 (2.4%) 5/164 (3.0%) 0.54 (0.18to 1.28) 0.43 (0.23 to 0.78) p < 0.05 1647371 Patients Heart DiseaseVEGF hCV- All Coronary 10.0627 0.0065 8.2097 0.0042 136/673 130/613(21.2%) 17/164 (10.4%) 0.46 (0.26 to 0.76) 1.06 (0.81 to 1.39) p <1647371 Patients Artery Bypass (20.2%) 0.005 or Revascularization VEGFhCV- All Total Coronary Heart 12.4873 0.0019 11.905 0.0006 249/673219/613 (35.7%) 37/164 (22.6%) 0.50 (0.33 to 0.73) 0.95 (0.75 to 1.19) p< 1647371 Patients Disease Events (37.0%) 0.005 VEGF hCV- AllCardiovascular 6.3554 0.0417 5.2451 0.022 39/673 (5.8%) 19/613 (3.1%)5/164 (3.0%) 0.51 (0.17 to 1.20) 0.52 (0.29 to 0.90) p < 0.05 1647371Patients Mortality VEGF hCV- All Fatal Atherosclerotic 6.3554 0.04175.2451 0.022 39/673 (5.8%) 19/613 (3.1%) 5/164 (3.0%) 0.51 (0.17 to1.20) 0.52 (0.29 to 0.90) p < 0.05 1647371 Patients CardiovascularDisease VEGF hCV- All Fatal/Nonfatal 8.0612 0.0178 7.7403 0.0054 277/673246/613 (40.1%) 48/164 (29.3%) 0.59 (0.41 to 0.85) 0.96 (0.77 to 1.20) p< 0.05 1647371 Patients Atherosclerotic (41.2%) CV Disease VEGF hCV- AllFatal Coronary 7.3992 0.0247 6.9861 0.0082 32/1030 (3.1%) 24/384 (6.3%)1/34 (2.9%) 0.95 (0.05 to 4.61) 2.08 (1.20 to 3.57) p < 0.05 791476Patients Heart Disease VEGF hCV- All Fatal/Nonfatal 6.5892 0.0371 5.95630.0147 66/1030 (6.4%) 26/384 (6.8%) 6/34 (17.6%) 3.13 (1.14 to 7.35)1.06 (0.65 to 1.68) p < 0.05 791476 Patients Cerebrovascular DiseaseVEGF hCV- All Cardiovascular 9.5492 0.0084 9.008 0.0027 34/1030 (3.3%)27/384 (7.0%) 2/34 (5.9%) 1.83 (0.29 to 6.39) 2.22 (1.31 to 3.72) p <791476 Patients Mortality 0.005 VEGF hCV- All Fatal Atherosclerotic9.5492 0.0084 9.008 0.0027 34/1030 (3.3%) 27/384 (7.0%) 2/34 (5.9%) 1.83(0.29 to 6.39) 2.22 (1.31 to 3.72) p < 791476 Patients Cardiovascular0.005 Disease VWF hCV- All MI (Fatal/Nonfatal) 4.2053 0.0403 4.15040.0416 178/1199 28/277 (10.1%) 0.65 (0.42 to 0.97) p < 0.05 7481138Patients (14.8%) VWF hCV- All Nonfatal MI 5.9933 0.0144 5.8657 0.0154170/1199 24/277 (8.7%) 0.57 (0.36 to 0.88) p < 0.05 7481138 Patients(Probable/Definite) (14.2%) VWF hCV- All Definite 4.4518 0.0349 4.35090.037 123/1199 17/277 (6.1%) 0.57 (0.33 to 0.94) p < 0.05 7481138Patients Nonfatal MI (103%) VWF hCV- All Nonfatal MI 6.0747 0.01375.9319 0.0149 160/1199 22/277 (7.9%) 0.56 (0.34 to 0.87) p < 0.057481138 Patients (def & prob) (13.3%) VWF hCV- All Fatal/Nonfatal 3.94650.047 3.898 0.0483 176/1199 28/277 (10.1%) 0.65 (0.42 to 0.98) p < 0.057481138 Patients MI (def & prob) (14.7%) VWF hCV- All History of 4.34050.0372 4.3128 0.0378 166/1199 52/277 (18.8%) 1.44 (1.01 to 2.02) p <0.05 7481138 Patients Diabetes (13.8%) VWF hCV- All CARE MI: 4.14 0.04194.047 0.0443 116/1199 16/276 (5.8%) 0.57 (0.32 to 0.96) p < 0.05 7481138Patients Non Q-Wave MI (9.7%) *Results of the Overall Score Test(chi-square test) for the logistic regression model in which thequalitative phenotype is a function of SNP genotype (based on placebopatients only). **Results of the chi-square test of the SNP effect(based on the logistic regression model for placebo patients only).

TABLE 7 Overall SNP Effect Placebo Patients Significant AssociationsBetween SNP Genotypes and Quantitative Phenotypes F-Test F-Test mean(se)# (N) Significance Public Marker Stratum Phenotype (at Baseline)statistic p-value statistic p-value 0 Rare Alleles 1 Rare Allele 2 RareAlleles Level HDLBP hCV22274624 All Patients Ln (Triglycerides) 5.550.004 5.5479 0.004 4.955 (0.014) (N = 802) 4.998 (0.016) (N = 545) 5.073(0.036) (N = 114) p < 0.005 HDLBP hCV22274624 All Patients VLDL 8 0.00047.9953 0.0004 25.969 (0.564) (N = 802) 27.873 (0.685) (N = 544) 32.000(1.497) (N = 114) p < 0.0005 HFE hCV1085600 All Patients Bilirubin,Total 3.93 0.0198 3.9303 0.0198 0.479 (0.007) (N = 1083) 0.509 (0.013)(N = 354) 0.561 (0.039) (N = 39) p < 0.05 HFE hCV1085600 All PatientsHemoglobin (gms %) 7.36 0.0007 7.3625 0.0007 14.808 (0.035) (N = 1071)15.040 (0.060) (N = 353) 15.213 (0.181) (N = 39) p < 0.005 HFEhCV1085600 All Patients Mean Cell Hemoglobin 15.49 <.0001 15.4903 <.000130.398 (0.054) (N = 1071) 30.956 (0.093) (N = 353) 31.113 (0.281) (N =39) p < 0.0005 LAMA2 hCV25990513 All Patients Left Ventricular Eject onFraction (%) 6.95 0.001 6.9481 0.001 53.735 (0.376) (N = 1058) 52.591(0.628) (N = 379) 46.632 (1.984) (N = 38) p < 0.005 PLG hCV25614474 AllPatients Systolic Blood Pressure (mmHg) 6.21 0.0021 6.2083 0.0021130.051 (0.671) (N = 738) 128.934 (0.731) (N = 622) 123.371 (1.780) (N =105) p < 0.005 MARK3 hCV25926178 All Patients Change from Baseline inUrinary 4.43 0.0121 4.4318 0.0121 0.053 (0.026) (N = 561) 0.101 (0.024)(N = 637) 0.196 (0.041) (N = 224) p < 0.05 Glucose (at LOCF) MARK3hCV25926178 All Patients Change from Baseline in Urinary 6.31 0.00196.3069 0.0019 0.069 (0.035) (N = 334) 0.064 (0.034) (N = 350) 0.277(0.054) (N = 141) p < 0.005 Glucose (at 5 Years) MARK3 hCV25926771 AllPatients Change from Baseline in Urinary 5.76 0.0165 5.7578 0.0165 0.050(0.026) (N = 556) 0.130 (0.021) (N = 864) p < 0.05 Glucose (at LOCF)PON2 hCV8952817 All Patients Baseline HDL 4.65 0.0097 4.6545 0.009738.486 (0.304) (N = 872) 39.530 (0.393) (N = 524) 41.122 (0.986) (N =83) p < 0.05 SN hCV2992252 All Patients Baseline Lymphocytes, Absolute(k/cumm) 5.24 0.0054 5.242 0.0054 2.334 (0.033) (N = 532) 2.282 (0.029)(N = 704) 2.135 (0.052) (N = 218) p < 0.05 SOAT2 hCV15962586 AllPatients Baseline HDL 3.41 0.0335 3.4055 0.0335 38.723 (0.283) (N =1007) 39.362 (0.434) (N = 430) 42.191 (1.405) (N = 41) p < 0.05 SOAT2hCV15962586 All Patients Baseline Ln (Triglycerides) 3.9 0.0204 3.90270.0204 4.995 (0.012) (N = 1007) 4.957 (0.019) (N = 430) 4.847 (0.060) (N= 41) p < 0.05 SOAT2 hCV15962586 All Patients Baseline 3.82 0.02223.8167 0.0222 27.787 (0.504) (N = 1006) 25.888 (0.771) (N = 430) 22.561(2.497) (N = 41) p < 0.05 SOAT2 hCV15962586 All Patients BaselineVLDL-Triglycerides 4.05 0.0175 4.0544 0.0175 125.268 (2.044) (N = 1004)117.305 (3.123) (N = 430) 103.537 (10.114) (N = 41) p < 0.05 * Resultsof the Overall F-Test for the analysis of variance model in which thequantitative phenotype is a function of SNP genotype (based on placebopatients only). ** Results of the F-test of the SNP effect (based on theanalysis of variance model for placebo patients only). # Least squaresestimates of the mean and its standard error based on the analysis ofvariance model.

TABLE 8 Overall* Interaction Effect** 0 Rare Alleles SignificantInteractions Between SNP Genotypes and Pravastatin Efficacy Chi-SquareTest Chi-Square n/total (%) Public Marker Stratum Phenotype statisticp-value statistic inter pv Prava ABCA1 hCV2741051 All PatientsFatal/Non-fatal Cerebrovascular 19.4858 0.0016 7.5666 0.0227 51/730(7.0%) Disease ABCA1 hCV2741051 All Patients Any Report of Stroke DuringCARE 20.2702 0.0011 8.3498 0.0154 27/730 (3.7%) ABCA1 hCV2741051 AllPatients 1st Stroke Occurred During CARE 19.1074 0.0018 7.1772 0.027626/730 (3.6%) AGTR1 hCV3187716 All Patients Fatal CHD/Definite Non-fatalMI 17.2109 0.0041 7.5975 0.0224 63/769 (8.2%) AGTR1 hCV3187716 AllPatients Hosp. for Unstable Angina 11.9501 0.0355 7.5586 0.0228 120/769(15.6%) AGTR1 hCV3187716 All Patients Total Coronary Heart DiseaseEvents 20.7576 0.0009 6.1362 0.0465 227/769 (29.5%) CCL11 hCV7449808 AllPatients Hosp. for Cardiovascular Disease 31.6672 <.0001 11.562 0.0031423/1025 (41.3%) CCL11 hCV7449808 All Patients Total Coronary HeartDisease Events 19.3552 0.0017 6.9384 0.0311 310/1025 (30.2%) CCL11hCV7449808 All Patients Total Cardiovascular Disease Events 32.1314<.0001 12.1479 0.0023 436/1025 (42.5%) CCL11 hCV7449808 All PatientsFatal/Non-fatal Atherosclerotic 24.1297 0.0002 6.6941 0.0352 359/1025(35.0%) Disease CV CHUK hCV1345898 All Patients Non-fatal MI (def &prob) 19.6476 0.0015 7.1993 0.0273 47/413 (11.4%) CHUK hCV1345898 AllPatients Hosp. for Unstable Angina 17.1525 0.0042 9.4908 0.0087 68/413(16.5%) CR1 hCV25598594 All Patients Fatal CHD/Definite Non-fatal MI15.4324 0.0015 5.4753 0.0193 139/1445 (9.6%) CR1 hCV25598594 AllPatients Non-fatal MI (def & prob) 16.765 0.0008 5.4291 0.0198 132/1445(9.1%) CR1 hCV25598594 All Patients Coronary Artery Bypass or 22.1947<.0001 5.6728 0.0172 212/1445 (14.7%) Revascularization CR1 hCV25598594All Patients Hosp. for Cardiovascular Disease 20.4621 0.0001 5.917 0.015586/1445 (40.6%) CR1 hCV25598594 All Patients Hosp. for Unstable Angina10.6553 0.01 37 4.7608 0.0291 223/1445 (15.4%) CR1 hCV25598594 AllPatients Total Coronary Heart Disease Events 21.4023 <.0001 10.02440.0015 431/1445 (29.8%) CR1 hCV25598594 All Patients TotalCardiovascular Disease Events 21.0456 0.0001 5.8723 0.0154 603/1445(41.7%) CR1 hCV25598594 All Patients Fatal/Non-fatal Atherosclerotic21.601 <.0001 9.255 0.0023 491/1445 (34.0%) Disease CV CXCL16 hCV8718197All Patients Fatal CHD/Definite Non-fatal MI 19.0205 0.0019 7.6339 0.02236/468 (7.7%) CXCL16 hCV8718197 All Patients Fatal/Non-fatal MI (def &prob) 23.7086 0.0002 9.3715 0.0092 33/468 (7.1%) CXCL16 hCV8718197 AllPatients Coronary Artery Bypass or 23.6046 0.0003 9.8539 0.0072 56/468(12.0%) Revascularization CXCL16 hCV8718197 All Patients Hosp. forCardiovascular Disease 20.8072 0.0009 6.1046 0.0473 1 77/468 (37.8%)CXCL16 hCV8718197 All Patients Total Coronary Heart Disease Events20.8149 0.0009 6.8483 0.0326 125/468 (26.7%) CXCL16 hCV8718197 AllPatients Cardiovascular Mortality 11.7405 0.0385 7.9556 0.0187 12/468(2.6%) CXCL16 hCV8718197 All Patients Total Cardiovascular DiseaseEvents 23.8178 0.0002 7.808 0.0202 180/468 (38.5%) CXCL16 hCV8718197 AllPatients Fatal Atherosclerotic Cardiovascular 12.2666 0.0313 8.01020.0182 12/468 (2.6%) Disease ELN hCV1253630 All Patients FatalCHD/Definite Non-fatal MI 18.1317 0.0028 8.1533 0.017 45/543 (8.3%) ELNhCV1253630 All Patients Non-fatal MI (def & prob) 20.2262 0.0011 10.31910.0057 42/543 (7.7%) ELN hCV1253630 All Patients Fatal/Non-fatal MI (def& prob) 27.8399 <.0001 13.5967 0.0011 45/543 (8.3%) ELN hCV1253630 AllPatients Hosp. for Cardiovascular Disease 21.4078 0.0007 7.3688 0.0251204/543 (37.6%) ELN hCV1253630 All Patients Total Coronary Heart DiseaseEvents 19.635 0.0015 8.2358 0.0163 146/543 (26.9%) ELN hCV1253630 AllPatients Total Cardiovascular Disease Events 21.3232 0.0007 6.42220.0403 212/543 (39.0%) HLA-DPA1 hCV15760070 All Patients Coronary ArteryBypass or 24.365 0.0002 7.073 0.0291 143/1019 (14.0%) RevascularizationHLA-DPA1 hCV15760070 All Patients Total Coronary Heart Disease Events20.3365 0.0011 9.1406 0.0104 285/1019 (28.0%) HLA-DPB1 hCV25651174 AllPatients Fatal CHD/Definite Non-fatal MI 15.7588 0.0076 6.9829 0.030558/733 (7.9%) HLA-DPB1 hCV25651174 All Patients Non-fatal MI (def &prob) 19.2761 0.0017 7.1578 0.0279 63/733 (8.6%) HLA-DPB1 hCV25651174All Patients Fatal/Non-fatal MI (def & prob) 22.2281 0.0005 8.61580.0135 65/733 (8.9%) HLA-DPB1 hCV25651174 All Patients Coronary ArteryBypass or 26.9669 <.0001 10.9893 0.0041 103/733 (14.1%)Revascularization HLA-DPB1 hCV25651174 All Patients Hosp. forCardiovascular Disease 27.7297 <.0001 7.3005 0.026 282/733 (38.5%)HLA-DPB1 hCV25651174 All Patients Total Coronary Heart Disease Events23.6497 0.0003 11.0762 0.0039 207/733 (28.2%) HLA-DPB1 hCV25651174 AllPatients Total Cardiovascular Disease Events 25.4895 0.0001 6.59850.0369 291/733 (39.7%) HLA-DPB1 hCV25651174 All Patients Fatal/Non-fatalAtherosclerotic CV 24.828 0.0002 10.0154 0.0067 230/733 (31.4%) DiseaseHLA-DPB1 hCV8851085 All Patients Fatal/Non-fatal MI (def & prob) 18.90460.002 6.0738 0.048 82/919 (8.9%) HLA-DPB1 hCV8851085 All PatientsCoronary Artery Bypass or 26.0775 <.0001 11.1434 0.0038 129/919 (14.0%)Revascularization HLA-DPB1 hCV8851085 All Patients Hosp. forCardiovascular Disease 23.3669 0.0003 6.8274 0.0329 363/919 (39.5%)HLA-DPB1 hCV8851085 All Patients Total Coronary Heart Disease Events21.0571 0.0008 8.5864 0.0137 263/919 (28.6%) HLA-DPB1 hCV8851085 AllPatients Total Cardiovascular Disease Events 23.3123 0.0003 6.96170.0308 374/919 (40.7%) HLA-DPB1 hCV8851085 All Patients Fatal/Non-fatalAtherosclerotic CV 22.7355 0.0004 8.8922 0.0117 301/919 (32.8%) DiseaseICAM1 hCV8726337 All Patients Non-fatal MI (def & prob) 18.3028 0.00268.2192 0.0164 28/495 (5.7%) ICAM1 hCV8726337 All PatientsFatal/Non-fatal MI (def & prob) 21.403 0.0007 8.3848 0.0151 31/495(6.3%) ICAM3 hCV25473653 All Patients Total Cardiovascular DiseaseEvents 23.2012 0.0003 6.7475 0.0343 376/924 (40.7%) ICAM3 hCV25473653All Patients Fatal/Non-fatal Atherosclerotic CV 21.6115 0.0006 7.31820.0258 299/924 (32.4%) Disease IGF2R hCV2200985 All Patients Hosp. forCardiovascular Disease 23.7283 0.0002 8.0478 0.0179 465/1175 (39.6%)IL1A hCV9546471 All Patients Total Mortality 12.1611 0.0326 10.36780.0056 52/759 (6.9%) IL1RN hCV8737990 All Patients Fatal CHD/DefiniteNon-fatal MI 16.7149 0.0051 7.1816 0.0276 80/809 (9.9%) IL1RN hCV8737990All Patients Non-fatal MI (def & prob) 20.9801 0.0008 7.2412 0.026868/809 (8.4%) IL1RN hCV8737990 All Patients Fatal/Non-fatal MI (def &prob) 22.5713 0.0004 7.6202 0.0221 76/809 (9.4%) IL1RN hCV8737990 AllPatients Hosp. for Cardiovascular Disease 25.4952 0.0001 7.1653 0.0278315/809 (38.9%) IL1RN hCV8737990 All Patients Total Coronary HeartDisease Events 23.5824 0.0003 10.6112 0.005 228/809 (28.2%) IL1RNhCV8737990 All Patients Total Cardiovascular Disease Events 24.66560.0002 6.7849 0.0336 325/809 (40.2%) IL1RN hCV8737990 All PatientsFatal/Non-fatal Atherosclerotic CV 24.3476 0.0002 9.5892 0.0083 260/809(32.1%) Disease IL6ST hCV16170435 All Patients Hosp. for CardiovascularDisease 20.5539 0.001 6.1238 0.0468 450/1131 (39.8%) IL6ST hCV16170435All Patients Total Cardiovascular Disease Events 21.8497 0.0006 6.40730.0406 465/1131 (41.1%) LRP8 hCV190754 All Patients Hosp. for UnstableAngina 14.1312 0.0148 9.6697 0.0079 98/560 (17.5%) MTRR hCV7580070 AllPatients Hosp. for Cardiovascular Disease 25.4655 0.0001 7.7684 0.0206466/1201 (38.8%) MTRR hCV7580070 All Patients Total Coronary HeartDisease Events 22.029 0.0005 7.6985 0.0213 338/1201 (28.1%) MTRRhCV7580070 All Patients Total Cardiovascular Disease Events 25.947<.0001 7.2212 0.027 480/1201 (40.0%) MTRR hCV7580070 All PatientsFatal/Non-fatal Atherosclerotic CV 25.0449 0.0001 8.5401 0.014 390/1201(32.5%) Disease NPC1 hCV25472673 All Patients Fatal CHD/DefiniteNon-fatal MI 16.7713 0.005 6.9147 0.0315 65/596 (10.9%) NPC1 hCV25472673All Patients Hosp. for Cardiovascular Disease 33.7727 <.0001 16.89660.0002 262/596 (44.0%) NPC1 hCV25472673 All Patients Total CoronaryHeart Disease Events 23.8979 0.0002 12.324 0.0021 193/596 (32.4%) NPC1hCV25472673 All Patients Total Cardiovascular Disease Events 36.5639<.0001 18.2781 0.0001 274/596 (46.0%) NPC1 hCV25472673 All PatientsFatal/Non-fatal Atherosclerotic CV 28.4984 <.0001 15.5441 0.0004 221/596(37.1%) Disease NPC1 hCV7490135 All Patients Hosp. for CardiovascularDisease 23.7333 0.0002 9.7365 0.0077 194/437 (44.4%) NPC1 hCV7490135 AllPatients Total Coronary Heart Disease Events 19.1385 0.0018 7.98240.0185 146/437 (33.4%) NPC1 hCV7490135 All Patients CardiovascularMortality 13.4221 0.0197 7.0589 0.0293 26/437 (5.9%) NPC1 hCV7490135 AllPatients Total Cardiovascular Disease Events 25.0799 0.0001 10.20930.0061 202/437 (46.2%) NPC1 hCV7490135 All Patients FatalAtherosclerotic Cardiovascular 12.5678 0.0278 6.6963 0.0351 25/437(5.7%) Disease NPC1 hCV7490135 All Patients Fatal/Non-fatalAtherosclerotic CV 21.1468 0.0008 9.3367 0.0094 165/437 (37.8%) DiseasePEMT hCV7443062 All Patients Fatal CHD/Definite Non-fatal MI 17.6580.0034 8.5923 0.0136 34/478 (7.1%) PLAU hCV16273460 All PatientsFatal/Non-fatal Atherosclerotic CV 18.1127 0.0028 6.1227 0.0468 301/903(33.3%) Disease PON1 hCV2548962 All Patients Total Coronary HeartDisease Events 16.8056 0.0049 6.2165 0.0447 217/736 (29.5%) PON1hCV2548962 All Patients Any Report of Stroke During CARE 34.8995 <.00017.1404 0.0281 13/736 (1.8%) PON1 hCV2548962 All Patients 1st StrokeOccurred During CARE 28.2289 <.0001 6.8104 0.0332 13/736 (1.8%) SELPhCV11975296 All Patients Coronary Artery Bypass or 24.9318 0.0001 7.38210.0249 146/969 (15.1%) Revascularization SELP hCV11975296 All PatientsHosp. for Cardiovascular Disease 27.7519 <.0001 6.7453 0.0343 415/969(42.8%) SELP hCV11975296 All Patients Hosp. for Unstable Angina 15.11320.0099 8.9591 0.0113 150/969 (15.5%) SERPINA1 hCV1260328 All PatientsFatal/Non-fatal Cerebrovascular 21.6532 0.0006 11.1964 0.0037 56/942(5.9%) Disease SERPINA1 hCV1260328 All Patients Any Report of StrokeDuring CARE 15.254 0.0093 7.0558 0.0294 27/942 (2.9%) TAP1 hCV549926 AllPatients Fatal CHD/Definite Non-fatal MI 16.2424 0.0062 6.4831 0.0391104/1042 (10.0%) TGFB1 hCV8708473 All Patients Fatal Coronary HeartDisease 19.8613 0.0013 16.4945 0.0003 36/704 (5.1%) TGFB1 hCV8708473 AllPatients Total Mortality 12.6344 0.0271 11.4639 0.0032 51/704 (7.2%)TGFB1 hCV8708473 All Patients Total Coronary Heart Disease Events27.3046 <.0001 8.436 0.0147 226/704 (32.1%) TGFB1 hCV8708473 AllPatients Cardiovascular Mortality 21.2405 0.0007 18.5606 <.0001 39/704(5.5%) TGFB1 hCV8708473 All Patients Fatal AtheroscleroticCardiovascular 20.614 0.001 17.9247 0.0001 38/704 (5.4%) Disease TGFB1hCV8708473 All Patients Fatal/Non-fatal Atherosclerotic CV 27.9483<.0001 8.0319 0.018 262/704 (37.2%) Disease TGFB1 hCV8708473 AllPatients More Than 1 Prior MI 14.8325 0.0111 12.9873 0.0015 122/704(17.3%) TGFB1 hCV8708473 All Patients History of Stroke 22.4625 0.00047.6883 0.0214 38/704 (5.4%) TGFB1 hCV8708473 All Patients Any Report ofStroke Prior 13.4403 0.0196 7.6397 0.0219 53/704 (7.5%) to or DuringCARE TLR5 hCV15871020 All Patients Hosp. for Cardiovascular Disease28.2057 <.0001 12.2152 0.0022 444/1087 (40.8%) TLR5 hCV15871020 AllPatients Total Coronary Heart Disease Events 26.4624 <.0001 13.20130.0014 331/1087 (30.5%) TLR5 hCV15871020 All Patients TotalCardiovascular Disease Events 28.9522 <.0001 12.4869 0.0019 457/1087(42.0%) TLR5 hCV15871020 All Patients Fatal/Non-fatal Atherosclerotic23.7163 0.0002 10.5837 0.005 374/1087 (34.4%) CV Disease TNF hCV7514879All Patients Total Mortality 11.4977 0.0424 6.8371 0.0328 63/1057 (6.0%)TNF hCV7514879 All Patients Fatal/Non-fatal MI (def & prob) 21.22630.0007 7.2562 0.0266 111/1057 (10.5%) TNF hCV7514879 All Patients Hosp.for Cardiovascular Disease 23.6158 0.0003 7.276 0.0263 432/1057 (40.9%)TNF hCV7514879 All Patients Total Cardiovascular Disease Events 24.22110.0002 7.3706 0.0251 448/1057 (42.4%) ABCC8 hCV600632 All PatientsCatheterization 13.9418 0.016 9.5561 0.0084 74/615 (12.0%) ADAMTS13hCV11571465 All Patients Nonfatal MI (Probable/Definite) 17.5811 0.00356.1707 0.0457 46/508 (9.1%) ADAMTS13 hCV11571465 All Patients NonfatalMI (def & prob) 17.3392 0.0039 6.5756 0.0373 46/508 (9.1%) ADAMTS13hCV11571465 All Patients Family History of CV Disease 14.4524 0.01311.1981 0.0037 191/508 (37.6%) APOE hCV905013 All Patients Nonfatal MI(Probable/Definite) 18.7262 0.0022 6.2618 0.0437 33/395 (8.4%) BCL2A1hCV7509650 All Patients MI (Fatal/Nonfatal) 20.7271 0.0009 7.0892 0.028975/828 (9.1%) BCL2A1 hCV7509650 All Patients Definite Nonfatal MI 15.7910.0075 7.0986 0.0287 52/828 (6.3%) BCL2A1 hCV7509650 All PatientsNonfatal MI (def & prob) 21.0159 0.0008 8.5271 0.0141 67/828 (8.1%)BCL2A1 hCV7509650 All Patients Fatal/Nonfatal MI (def & prob) 21.98310.0005 8.1075 0.0174 72/828 (8.7%) CCL4 hCV12120554 All Patients FatalCoronary Heart Disease 17.031 0.0007 9.227 0.0024 38/1093 (3.5%) CCL4hCV12120554 All Patients Total Mortality 13.1127 0.0044 9.1894 0.002466/1093 (6.0%) CCL4 hCV12120554 All Patients Total Coronary HeartDisease Events 17.7584 0.0005 6.5889 0.0103 333/1093 (30.5%) CCL4hCV12120554 All Patients Cardiovascular Mortality 18.0677 0.0004 10.60310.0011 44/1093 (4.0%) CCL4 hCV12120554 All Patients FatalAtherosclerotic 19.0598 0.0003 11.5967 0.0007 44/1093 (4.0%)Cardiovascular Disease CCL4 hCV12120554 All Patients Fatal/NonfatalAtherosclerotic 19.4099 0.0002 6.6292 0.01 376/1093 (34.4%) CV DiseaseCD6 hCV2553030 All Patients Hosp. for Cardiovascular Disease 20.60030.001 6.0367 0.0489 351/845 (41.5%) CD6 hCV2553030 All Patients TotalCardiovascular Disease Events 21.3941 0.0007 6.0879 0.0476 365/845(43.2%) CD6 hCV2553030 All Patients History of Angina Pectoris 12.50020.0285 11.4198 0.0033 180/845 (21.3%) CD6 hCV25922320 All PatientsDefinite Nonfatal MI 15.6195 0.008 6.8415 0.0327 57/995 (5.7%) CD6hCV25922320 All Patients Fatal CHD/Definite Nonfatal MI 17.6754 0.00348.5308 0.014 77/995 (7.7%) COL11A1 hCV8400671 All Patients MI(Fatal/Nonfatal) 18.8839 0.002 6.1759 0.0456 108/1007 (10.7%) COL11A1hCV8400671 All Patients Nonfatal MI (def & prob) 19.0171 0.0019 7.45110.0241 97/1007 (9.6%) COL11A1 hCV8400671 All Patients Fatal/Nonfatal MI(def & prob) 20.2734 0.0011 7.2186 0.0271 107/1007 (10.6%) CYP4F2hCV16179493 All Patients Catheterization 16.4595 0.0056 9.206 0.0176/724 (10.5%) CYP4F2 hCV16179493 All Patients Fatal Coronary HeartDisease 14.8471 0.011 11.1566 0.0038 18/724 (2.5%) CYP4F2 hCV16179493All Patients Total Mortality 13.9492 0.0159 8.7397 0.0127 34/724 (4.7%)CYP4F2 hCV16179493 All Patients Cardiovascular Mortality 12.7875 0.02557.6593 0.0217 24/724 (3.3%) CYP4F2 hCV16179493 All Patients FatalAtherosclerotic 13.275 0.209 8.1604 0.0169 23/724 (3.2%) CardiovascularDisease FCGR2A hCV9077561 All Patients Catheterization 17.7696 0.003212.6158 0.0018 43/372 (11.6%) FCGR2A hCV9077561 All Patients CoronaryArtery Bypass or 21.2433 0.0007 7.357 0.0253 60/372 (16.1%)Revascularization GAPD hCV8921288 All Patients MI (Fatal/Nonfatal)19.0929 0.0018 7.4744 0.0238 106/975 (10.9%) GAPD hCV8921288 AllPatients Nonfatal MI (Probable/Definite) 17.0899 0.0043 6.5106 0.0386100/975 (10.3%) GAPD hCV8921288 All Patients Fatal CHD/Definite NonfatalMI 18.5634 0.0023 10.4472 0.0054 102/975 (10.5%) GAPD hCV8921288 AllPatients Nonfatal MI (def & prob) 14.4084 0.0132 6.4562 0.0396 97/975(9.9%) GAPD hCV8921288 All Patients Fatal/Nonfatal MI (def & prob)19.0127 0.0019 6.6952 0.0352 103/975 (10.6%) IL12A hCV16053900 AllPatients Coronary Artery Bypass Graft 18.6383 0.0022 8.9976 0.011122/453 (4.9%) IL12A hCV16053900 All Patients Coronary Artery Bypass or29.621 <.0001 13.1691 0.0014 50/453 (11.0%) Revascularization IL9hCV3275199 All Patients MI (Fatal/Nonfatal) 22.6018 0.0004 10.10510.0064 125/1129 (11.1%) IL9 hCV3275199 All Patients Nonfatal MI(Probable/Definite) 23.2912 0.0003 11.1902 0.0037 117/1129 (10.4%) IL9hCV3275199 All Patients Nonfatal MI (def & prob) 19.7567 0.0014 9.22620.0099 111/1129 (9.8%) IL9 hCV3275199 All Patients Fatal/Nonfatal MI(def & prob) 22.278 0.0005 9.1717 0.0102 122/1129 (10.8%) KLK14hCV16044337 All Patients MI (Fatal/Nonfatal) 27.4658 <.0001 8.606 0.013570/693 (10.1%) KLK14 hCV16044337 All Patients Nonfatal MI(Probable/Definite) 25.1331 0.0001 8.1765 0.0168 67/693 (9.7%) KLK14hCV16044337 All Patients Definite Nonfatal MI 18.9026 0.002 6.7602 0.03449/693 (7.1%) KLK14 hCV16044337 All Patients Coronary Artery BypassGraft 18.8672 0.002 8.7354 0.0127 60/693 (8.7%) KLK14 hCV16044337 AllPatients Fatal CHD/Definite Nonfatal MI 23.3389 0.0003 9.6221 0.008166/693 (9.5%) KLK14 hCV16044337 All Patients Nonfatal MI (def & prob)23.6296 0.0003 7.6653 0.0217 63/693 (9.1%) KLK14 hCV16044337 AllPatients Fatal/Nonfatal MI (def & prob) 28.3799 <.0001 8.3321 0.015568/693 (9.8%) LAMA5 hCV25629492 All Patients Definite Nonfatal MI 17.0520.0044 8.4868 0.0144 55/622 (8.8%) LAMA5 hCV25629492 All PatientsNonfatal MI (def & prob) 19.6962 0.0014 8.0144 0.0182 70/622 (11.3%)LAMA5 hCV25629492 All Patients Fatal/Nonfatal MI (def & prob) 21.13430.0008 6.1961 0.0451 75/622 (12.1%) MARK3 hCV25926771 All PatientsDefinite Nonfatal MI 17.5176 0.0015 3.8996 0.0483 39/578 (6.7%) MARK3hCV25926771 All Patients Fatal CHD/Definite Nonfatal MI 14.4978 0.00594.1405 0.0419 57/578 (9.9%) MJD hCV16189421 All Patients MI(Fatal/Nonfatal) 16.398 0.0058 6.2348 0.0443 73/845 (8.6%) MJDhCV16189421 All Patients Nonfatal MI (Probable/Definite) 16.5163 0.00557.157 0.0279 68/845 (8.0%) MJD hCV16189421 All Patients Nonfatal MI (def& prob) 17.6259 0.0035 9.9522 0.0069 63/845 (7.5%) MJD hCV16189421 AllPatients Fatal/Nonfatal MI (def & prob) 16.788 0.0049 6.31 0.0426 71/845(8.4%) MJD hCV16189421 All Patients Hosp. for Unstable Angina 11.2290.047 6.7739 0.0338 122/845 (14.4%) MMP27 hCV7492601 All PatientsPercutaneous Transluminal 13.2841 0.0209 6.4349 0.0401 42/432 (9.7%)Coronary Angioplasty NID2 hCV15876071 All Patients Fatal/Non-fatalCerebrovascular 13.2979 0.0207 7.6501 0.0218 47/830 (5.7%) DiseasePECAM1 hCV16170911 All Patients Stroke 16.5925 0.0053 7.4654 0.02397/476 (1.5%) PLAB hCV7494810 All Patients MI (Fatal/Nonfatal) 21.52160.0006 6.8687 0.0322 99/876 (11.3%) PLAB hCV7494810 All PatientsNonfatal MI (Probable/Definite) 19.4685 0.0016 6.2388 0.0442 93/876(10.6%) PLAB hCV7494810 All Patients Definite Nonfatal MI 19.0196 0.00198.9516 0.0114 69/876 (7.9%) PLAB hCV7494810 All Patients FatalCHD/Definite Nonfatal MI 18.025 0.0029 6.5222 0.0383 91/876 (10.4%) PLABhCV7494810 All Patients Nonfatal MI (def & prob) 18.3495 0.0025 6.81820.0331 89/876 (10.2%) PLAB hCV7494810 All Patients Fatal/Nonfatal MI(def & prob) 21.1333 0.0008 6.0322 0.049 96/876 (11.0%) PTPN21hCV16182835 All Patients Fatal/Non-fatal Cerebrovascular 15.5999 0.00818.6004 0.0136 38/661 (5.7%) Disease PTPN21 hCV25942539 All PatientsFatal/Non-fatal Cerebrovascular 14.0688 0.0152 7.0712 0.0291 38/672(5.7%) Disease QSCN6 hCV25761292 All Patients Coronary Artery BypassGraft 19.4949 0.0016 7.7834 0.0204 63/1085 (5.8%) SERPINA1 hCV25640505All Patients Coronary Artery Bypass Graft 20.6685 0.0009 7.2873 0.026244/724 (6.1%) SERPINB6 hCV16190893 All Patients Fatal/NonfatalAtherosclerotic CV 21.4112 0.0007 6.2956 0.0429 266/762 (34.9%) DiseaseSN hCV25623265 All Patients Definite Nonfatal MI 17.7417 0.0033 8.31140.0157 33/401 (8.2%) SN hCV25623265 All Patients PercutaneousTransluminal 12.2825 0.0311 7.1894 0.0275 30/401 (7.5%) CoronaryAngioplasty SN hCV25623265 All Patients Fatal CHD/Definite Nonfatal MI18.5351 0.0023 8.1295 0.0172 39/401 (9.7%) SN hCV25623265 All PatientsCoronary Artery Bypass or 27.1389 <.0001 8.407 0.0149 52/401 (13.0%)Revascularization SN hCV25623265 All Patients Total Coronary HeartDisease Events 18.4965 0.0024 6.233 0.0443 109/401 (27.2%) TGFB1hCV22272997 All Patients Fatal Coronary Heart Disease 17.2829 0.00414.9163 0.0006 29/554 (5.2%) TGFB1 hCV22272997 All Patients TotalMortality 15.1303 0.0098 13.5508 0.0011 41/554 (7.4%) TGFB1 hCV22272997All Patients Total Coronary Heart Disease Events 22.2798 0.0005 8.40790.0149 180/554 (32.5%) TGFB1 hCV22272997 All Patients CardiovascularMortality 18.1724 0.0027 16.0606 0.0003 31/554 (5.6%) TGFB1 hCV22272997All Patients Fatal Atherosclerotic Cardiovascular 19.1187 0.0018 16.69880.0002 31/554 (5.6%) Disease TLR6 hCV1180648 All Patients Fatal CoronaryHeart Disease 17.8186 0.0032 9.4953 0.0087 18/548 (3.3%) TLR6 hCV1180648All Patients Cardiovascular Mortality 17.2547 0.004 10.936 0.0042 19/548(3.5%) TLR6 hCV1180648 All Patients Fatal Atherosclerotic Cardiovascular15.9494 0.007 10.159 0.0062 19/548 (3.5%) Disease VEGF hCV791476 AllPatients Cardiovascular Mortality 13.8606 0.0165 9.7311 0.0077 45/1067(4.2%) VEGF hCV791476 All Patients Fatal Atherosclerotic Cardiovascular13.8845 0.0164 9.3771 0.0092 44/1067 (4.1%) Disease SignificantInteractions Between SNP Genotypes and Pravastatin 0 Rare Alleles 1 RareAllele 2 Rare Alleles Prava vs. Placebo Efficacy n/total (%) n/total (%)n/total (%) Odds Ratio (95% CI) Significance Public Placebo PravaPlacebo Prava Placebo 0 Rare Alleles 1 Rare Alleles 2 Rare Alleles LevelABCA1 53/746 (7.1%) 18/651 (2.8%) 38/615 (6.2%) 3/127 (2.4%) 9/107(8.4%) 0.98 (0.66 to 1.46) 0.43 (0.18 to 1.01) 0.26 (0.06 to 1.15) p <0.05 ABCA1 5/651 (0.8%) 22/615 (3.6%) 2/127 (1.6%) 7/107 (6.5%) 0.92(0.54 to 1.56) 0.21 (0.06 to 0.75) 0.23 (0.04 to 1.38) p < 0.05 ABCA130/746 (4.0%) 5/651 (0.8%) 18/615 (2.9%) 2/127 (1.6%) 7/107 (6.5%) 0.98(0.57 to 1.70) 0.26 (0.07 to 0.96) 0.23 (0.04 to 1.40) p < 0.05 AGTR127/746 (3.6%) 72/625 (11.5%) 71/588 (12.1%) 5/120 (4.2%) 23/150 (15.3%)0.63 (0.45 to 0.89) 0.95 (0.50 to 1.78) 0.24 (0.08 to 0.74) p < 0.05AGTR1 91/735 (12.4%) 103/625 (16.5%) 106/588 (18.0%) 8/120 (6.7%) 31/150(20.7%) 0.89 (0.68 to 1.17) 0.90 (0.53 to 1.52) 0.27 (0.11 to 0.69) p <0.05 AGTR1 126/735 (17.1%) 194/625 (31.0%) 208/588 (35.4%) 20/120(16.7%) 52/150 (34.7%) 0.80 (0.65 to 1.00) 0.82 (0.54 to 1.25) 0.38(0.19 to 0.74) p < 0.05 CCL11 252/735 (34.3%) 176/448 (39.3%) 171/412(41.5%) 9/34 (26.5%) 34/49 (69.4%) 0.76 (0.64 to 0.91) 0.91 (0.62 to1.35) 0.16 (0.06 to 0.44) p < 0.005 CCL11 483/1006 (48.0%) 127/448(28.3%) 132/412 (32.0%) 4/34 (11.8%) 22/49 (44.9%) 0.80 (0.66 to 0.96)0.84 (0.56 to 1.27) 0.16 (0.05 to 0.56) p < 0.05 CCL11 355/1006 (35.3%)181/448 (40.4%) 179/412 (43.4%) 9/34 (26.5%) 35/49 (71.4%) 0.77 (0.64 to0.91) 0.88 (0.60 to 1.30) 0.14 (0.05 to 0.40) p < 0.005 CCL11 494/1006(49.1%) 139/448 (31.0%) 146/412 (35.4%) 7/34 (20.6%) 27/49 (55.1%) 0.80(0.67 to 0.96) 0.82 (0.55 to 1.22) 0.21 (0.07 to 0.60) p < 0.05 CHUK405/1006 (40.3%) 69/734 (9.4%) 86/724 (11.9%) 17/354 (4.8%) 43/331(13.0%) 0.86 (0.56 to 1.30) 0.77 (0.37 to 1.61) 0.34 (0.14 to 0.81) p <0.05 CHUK 110/734 (15.0%) 136/724 (18.8%) 51/354 (14.4%) 73/331 (22.1%)1.38 (0.93 to 2.04) 0.76 (0.38 to 1.51) 0.59 (0.28 to 1.25) p < 0.05 CR153/407 (13.0%) 1/72 (1.4%) 12166 (18.2%) 0/0 (0.0%) 0/0 (0.0%) 0.76(0.60 to 0.97) 0.06 (0.01 to 0.52) p < 0.05 CR1 51/407 (12.5%) 2172(2.8%) 1 3/66 (1 9.7%) 0/0 (0.0%) 0/0 (0.0%) 0.74 (0.58 to 0.93) 0.12(0.02 to 0.56) p < 0.05 CR1 173/1413 (12.2%) 7/72 (9.7%) 21/66 (31.8%)0/0 (0.0%) 0/0 (0.0%) 0.74 (0.61 to 0.90) 0.23 (0.09 to 0.62) p < 0.05CR1 170/1413 (12.0%) 23/72 (31.9%) 39/66 (59.1%) 0/0 (0.0%) 0/0 (0.0%)0.79 (0.68 to 0.91) 0.33 (0.16 to 0.68) p < 0.05 CR1 267/1413 (18.9%)8/72 (11.1%) 19/66 (28.8%) 0/0 (0.0%) 0/0 (0.0%) 0.87 (0.71 to 1.06)0.31 (0.12 to 0.81) p < 0.05 CR1 11/72 (15.3%) 30/66 (45.5%) 0/0 (0.0%)0/0 (0.0%) 0.81 (0.69 to 0.95) 0.22 (0.09 to 0.50) p < 0.005 CR1656/1413 (46.4%) 24/72 (33.3%) 40/66 (60.6%) 0/0 (0.0%) 0/0 (0.0%) 0.78(0.68 to 0.91) 0.33 (0.16 to 0.68) p < 0.05 CR1 245/1413 (17.3%) 15/72(20.8%) 34/66 (51.5%) 0/0 (0.0%) 0/0 (0.0%) 0.81 (0.69 to 0.94) 0.25(0.11 to 0.54) p < 0.005 CXCL16 485/1413 (34.3%) 68/742 (9.2%) 79/722(10.9%) 34/292 (11.6%) 31/278 (11.2%) 0.44 (0.29 to 0.68) 0.82 (0.40 to1.70) 1.05 (0.46 to 2.40) p < 0.05 CXCL16 675/1413 (47.8%) 75/742(10.1%) 89/722 (1 2.3%) 36/292 (12.3%) 37/278 (13.3%) 0.38 (0.25 to0.58) 0.80 (0.39 to 1.66) 0.92 (0.40 to 2.08) p < 0.05 CXCL16 550/1413(38.9%) 119/742 (16.0%) 123/722 (17.0%) 43/292 (14.7%) 55/278 (19.8%)0.45 (0.32 to 0.65) 0.93 (0.51 to 1.71) 0.70 (0.35 to 1.41) p < 0.05CXCL16 305/742 (41.1%) 318/722 (44.0%) 124/292 (42.5%) 133/278 (47.8%)0.59 (0.45 to 0.76) 0.89 (0.56 to 1.40) 0.80 (0.48 to 1.36) p < 0.05CXCL16 74/469 (15.8%) 220/742 (29.6%) 227/722 (31.4%) 94/292 (32.2%)102/278 (36.7%) 0.57 (0.44 to 0.76) 0.92 (0.56 to 1.50) 0.82 (0.47 to1.43) p < 0.05 CXCL16 78/469 (1 6.6%) 24/742 (3.2%) 29/722 (4.0%) 19/292(6.5%) 9/278 (3.2%) 0.45 (0.22 to 0.90) 0.80 (0.24 to 2.64) 2.08 (0.55to 7.91) p < 0.05 CXCL16 108/469 (23.0%) 314/742 (42.3%) 325/722 (45.0%)130/292 (44.5%) 138/278 (49.6%) 0.56 (0.43 to 0.73) 0.90 (0.57 to 1.42)0.81 (0.48 to 1.38) p < 0.05 CXCL16 23/742 (3.1%) 29/722 (4.0%) 19/292(6.5%) 9/278 (3.2%) 0.45 (0.22 to 0.90) 0.76 (0.23 to 2.53) 2.08 (0.55to 7.91) p < 0.05 ELN 239/469 (51.0%) 65/724 (9.0%) 84/721 (11.7%)29/245 (11.8%) 21/241 (8.7%) 0.50 (0.34 to 0.75) 0.75 (0.37 to 1.49)1.41 (0.60 to 3.27) p < 0.05 ELN 182/469 (38.8%) 62/724 (8.6%) 88/721(12.2%) 30/245 (12.2%) 19/241 (7.9%) 0.50 (0.33 to 0.74) 0.67 (0.33 to1.37) 1.63 (0.69 to 3.87) p < 0.05 ELN 26/469 (5.5%) 68/724 (9.4%)95/721 (13.2%) 33/245 (13.5%) 21/241 (8.7%) 0.44 (0.30 to 0.65) 0.68(0.35 to 1.34) 1.63 (0.71 to 3.72) p < 0.005 ELN 247/469 (52.7%) 291/724(41.2%) 339/721 (47.0%) 113/245 (46.1%) 103/241 (42.7%) 0.63 (0.49 to0.80) 0.76 (0.49 to 1.18) 1.15 (0.68 to 1.95) p < 0.05 ELN 26/469 (5.5%)206/724 (28.5%) 254/721 (35.2%) 88/245 (35.9%) 74/241 (30.7%) 0.66 (0.51to 0.85) 0.73 (0.46 to 1.17) 1.23 (0.72 to 2.21) p < 0.05 ELN 298/724(41.2%) 348/721 (48.3%) 115/245 (46.9%) 107/241 (44.4%) 0.63 (0.50 to0.81) 0.75 (0.48 to 1.16) 1.11 (0.65 to 1.88) p < 0.05 HLA-DPA1 77/507(15.2%) 67/443 (15.1%) 86/429 (20.0%) 9/52 (17.3%) 2/56 (3.6%) 0.65(0.51 to 0.82) 0.71 (0.43 to 1.18) 5.65 (1.11 to 28.71) p < 0.05HLA-DPA1 73/507 (14.4%) 136/443 (30.7%) 146/429 (34.0%) 21/52 (40.4%)12/56 (21.4%) 0.69 (0.57 to 0.84) 0.86 (0.57 to 1.29) 2.48 (1.01 to6.08) p < 0.05 HLA-DPB1 86/507 (17.0%) 62/632 (9.8%) 81/632 (12.8%)20/144 (13.9%) 11/132 (8.3%) 0.57 (0.40 to 0.80) 0.74 (0.39 to 1.40)1.77 (0.69 to 4.56) p < 0.05 HLA-DPB1 248/507 (48.9%) 55/632 (8.7%)78/632 (12.3%) 16/144 (11.1%) 7/132 (5.3%) 0.59 (0.42 to 0.82) 0.68(0.36 to 1.28) 2.23 (0.77 to 6.43) p < 0.05 HLA-DPB1 182/507 (35.9%)61/632 (9.7%) 87/632 (13.8%) 20/144 (13.9%) 10/132 (7.6%) 0.54 (0.39 to0.75) 0.67 (0.36 to 1.24) 1.97 (0.76 to 5.07) p < 0.05 HLA-DPB1 255/507(50.3%) 87/632 (13.8%) 137/632 (21.7%) 27/144 (18.8%) 13/132 (9.8%) 0.68(0.52 to 0.90) 0.58 (0.34 to 0.98) 2.11 (0.92 to 4.86) p < 0.005HLA-DPB1 200/994 (20.1%) 259/632 (41.0%) 314/632 (49.7%) 61/144 (42.4%)45/132 (34.1%) 0.70 (0.57 to 0.86) 0.70 (0.47 to 1.05) 1.42 (0.79 to2.56) p < 0.05 HLA-DPB1 182/632 (28.8%) 225/632 (35.6%) 50/144 (34.7%)30/132 (22.7%) 0.69 (0.55 to 0.86) 0.73 (0.48 to 1.12) 1.81 (0.96 to3.42) p < 0.005 HLA-DPB1 357/994 (35.9%) 265/632 (41.9%) 318/632 (50.3%)64/144 (44.4%) 49/132 (37.1%) 0.69 (0.56 to 0.85) 0.71 (0.48 to 1.06)1.35 (0.76 to 2.43) p < 0.05 HLA-DPB1 93/708 (13.1%) 218/632 (34.5%)255/632 (40.3%) 54/144 (37.5%) 36/132 (27.3%) 0.66 (0.53 to 0.81) 0.78(0.52 to 1.17) 1.60 (0.87 to 2.95) p < 0.05 HLA-DPB1 98/708 (13.8%)53/521 (10.2%) 66/506 (13.0%) 11/73 (15.1%) 6/76 (7.9%) 0.57 (0.42 to0.76) 0.75 (0.42 to 1.37) 2.07 (0.66 to 6.51) p < 0.05 HLA-DPB1 108/708(15.3%) 72/521 (13.8%) 107/506 (21.1%) 11/73 (23.3%) 6/76 (7.9%) 0.68(0.53 to 0.87) 0.60 (0.36 to 0.99) 3.54 (1.22 to 10.31) p < 0.005HLA-DPB1 137/708 (19.4%) 209/521 (40.1%) 241/506 (47.6%) 33/73 (45.2%)24/76 (31.6%) 0.71 (0.59 to 0.86) 0.74 (0.50 to 1.08) 1.79 (0.86 to3.71) p < 0.05 HLA-DPB1 151/521 (29.0%) 177/506 (35.0%) 26/73 (35.6%)15/76 (19.7%) 0.72 (0.59 to 0.87) 0.76 (0.50 to 1.14) 2.25 (1.01 to5.02) p < 0.05 HLA-DPB1 334/708 (47.2%) 214/521 (41.1%) 246/506 (48.6%)35/73 (47.9%) 26/76 (34.2%) 0.70 (0.59 to 0.85) 0.74 (0.50 to 1.08) 1.77(0.86 to 3.65) p < 0.05 HLA-DPB1 258/708 (36.4%) 174/521 (33.4%) 197/506(38.9%) 29/73 (39.7%) 18/76 (23.7%) 0.70 (0.58 to 0.85) 0.79 (0.53 to1.17) 2.12 (0.98 to 4.57) p < 0.05 ICAM1 346/708 (48.9%) 76/736 (10.3%)91/749 (12.1%) 30/282 (10.6%) 30/268 (11.2%) 0.39 (0.25 to 0.63) 0.83(0.38 to 1.82) 0.94 (0.39 to 2.31) p < 0.05 ICAM1 291/708 (41.1%) 84/736(11.4%) 99/749 (13.2%) 31/282 (11.0%) 37/268 (13.8%) 0.39 (0.25 to 0.60)0.85 (0.40 to 1.79) 0.77 (0.33 to 1.80) p < 0.05 ICAM3 230/511 (45.0%)247/527 (46.9%) 19/70 (27.1%) 31/62 (50.0%) 0.71 (0.59 to 0.86) 0.93(0.63 to 1.36) 0.37 (0.17 to 0.82) p < 0.05 ICAM3 132/894 (14.8%)191/511 (37.4%) 201/527 (38.1%) 14/70 (20.0%) 25/62 (40.3%) 0.71 (0.58to 0.86) 0.97 (0.65 to 1.44) 0.37 (0.16 to 0.85) p < 0.05 IGF2R 174/894(19.5%) 137/316 (43.4%) 167/358 (46.6%) 5/24 (20.8%) 15/22 (68.2%) 0.75(0.63 to 0.88) 0.88 (0.59 to 1.31) 0.12 (0.03 to 0.48) p < 0.05 IL1A28/617 (4.5%) 43/584 (7.4%) 4/132 (3.0%) 14/144 (9.7%) 1.40 (0.90 to2.15) 0.60 (0.25 to 1.40) 0.29 (0.08 to 1.10) p < 0.05 IL1RN 428/894(47.9%) 44/585 (7.5%) 77/568 (13.6%) 15/121 (12.4%) 8/115 (7.0%) 0.75(0.55 to 1.03) 0.52 (0.28 to 0.97) 1.89 (0.68 to 5.27) p < 0.05 IL1RN321/894 (35.9%) 45/585 (7.7%) 78/568 (13.7%) 20/121 (16.5%) 12/115(10.4%) 0.68 (0.49 to 0.95) 0.52 (0.28 to 1.00) 1.70 (0.68 to 4.28) p <0.05 IL1RN 441/894 (49.3%) 49/585 (8.4%) 86/568 (15.1%) 20/121 (16.5%)12/115 (10.4%) 0.66 (0.48 to 0.90) 0.51 (0.28 to 0.94) 1.70 (0.69 to4.21) p < 0.05 IL1RN 367/894 (41.1%) 232/585 (39.7%) 288/568 (50.7%)60/121 (9.6%) 48/115 (41.7%) 0.77 (0.63 to 0.94) 0.64 (0.43 to 0.95)1.37 (0.75 to 2.51) p < 0.05 IL1RN 167/585 (28.5%) 213/568 (37.5%)45/121 (37.2%) 28/115 (24.3%) 0.74 (0.60 to 0.92) 0.67 (0.44 to 1.01)1.84 (0.96 to 3.54) p < 0.05 IL1RN 61/460 (13.3%) 239/585 (40.9%)293/568 (51.6%) 61/121 (50.4%) 49/115 (42.6%) 0.75 (0.62 to 0.92) 0.65(0.44 to 0.96) 1.37 (0.75 to 2.50) p < 0.05 IL1RN 68/460 (14.8%) 193/585(33.0%) 243/568 (42.8%) 51/121 (42.1%) 35/115 (30.4%) 0.75 (0.61 to0.93) 0.66 (0.44 to 0.99) 1.67 (0.89 to 3.12) p < 0.05 IL6ST 429/874(49.1%) 139/340 (40.9%) 173/352 (49.1%) 19/37 (51.4%) 11/37 (29.7%) 0.75(0.63 to 0.89) 0.72 (0.48 to 1.07) 2.49 (0.93 to 6.72) p < 0.05 IL6ST352/874 (40.3%) 142/340 (41.8%) 180/352 (51.1%) 19/37 (51.4%) 11/37(29.7%) 0.75 (0.64 to 0.89) 0.69 (0.46 to 1.02) 2.49 (0.93 to 6.72) p <0.05 LRP8 100/712 (14.0%) 130/687 (18.9%) 32/244 (13.1%) 51/235 (21.7%)1.21 (0.88 to 1.67) 0.70 (0.39 to 1.25) 0.54 (0.27 to 1.10) p < 0.05MTRR 510/1093 (46.7%) 135/284 (47.5%) 127/273 (46.5%) 5/22 (22.7%) 16/28(57.1%) 0.71 (0.61 to 0.84) 1.04 (0.68 to 1.59) 0.22 (0.06 to 0.79) p <0.05 MTRR 37/739 (5.0%) 98/284 (34.5%) 94/273 (34.4%) 2/22 (9.1%) 13/28(46.4%) 0.73 (0.62 to 0.87) 1.00 (0.64 to 1.56) 0.12 (0.02 to 0.60) p <0.05 MTRR 100/786 (12.7%) 137/284 (48.2%) 131/273 (48.0%) 5/22 (22.7%)16/28 (57.1%) 0.71 (0.60 to 0.84) 1.01 (0.66 to 1.54) 0.22 (0.06 to0.79) p < 0.05 MTRR 93/786 (11.8%) 110/284 (38.7%) 109/273 (39.9%) 2/22(9.1%) 15/28 (53.6%) 0.74 (0.63 to 0.88) 0.95 (0.62 to 1.46) 0.09 (0.02to 0.45) p < 0.05 NPC1 107/786 (13.6%) 56/664 (8.4%) 86/697 (12.3%)19/242 (7.9%) 36/208 (1 7.3%) 1.00 (0.69 to 1.45) 0.65 (0.33 to 1.30)0.41 (0.18 to 0.94) p < 0.05 NPC1 357/786 (45.4%) 255/664 (38.4%)323/697 (46.3%) 88/242 (36.4%) 122/208 (58.7%) 1.02 (0.81 to 1.28) 0.72(0.47 to 1.11) 0.40 (0.24 to 0.68) p < 0.0005 NPC1 272/786 (34.6%)186/664 (28.0%) 242/697 (34.7%) 59/242 (24.4%) 88/208 (42.3%) 1.01 (0.79to 1.29) 0.73 (0.46 to 1.15) 0.44 (0.25 to 0.77) p < 0.005 NPC1 370/786(47.1%) 259/664 (39.0%) 330/697 (47.3%) 90/242 (37.2%) 125/208 (60.1%)1.03 (0.81 to 1.29) 0.71 (0.46 to 1.09) 0.39 (0.23 to 0.67) p < 0.0005NPC1 303/786 (38.5%) 213/664 (32.1%) 274/697 (39.3%) 68/242 (28.1%)101/208 (48.6%) 1.03 (0.81 to 1.31) 0.73 (0.47 to 1.13) 0.41 (0.24 to0.71) p < 0.0005 NPC1 295/742 (39.8%) 333/718 (46.4%) 117/324 (36.1%)174/335 (51.9%) 1.01 (0.77 to 1.32) 0.76 (0.47 to 1.23) 0.52 (0.31 to0.89) p < 0.05 NPC1 506/1080 (46.9%) 213/742 (28.7%) 257/718 (35.8%)81/324 (25.0%) 122/335 (36.4%) 1.07 (0.80 to 1.42) 0.72 (0.44 to 1.20)0.58 (0.33 to 1.03) p < 0.05 NPC1 519/1080 (48.1%) 26/742 (3.5%) 30/718(4.2%) 3/324 (0.9%) 15/335 (4.5%) 1.30 (0.71 to 2.39) 0.83 (0.27 to2.53) 0.20 (0.04 to 0.97) p < 0.05 NPC1 83/557 (14.9%) 303/742 (40.8%)343/718 (47.8%) 119/324 (36.7%) 177/335 (52.8%) 1.02 (0.77 to 1.33) 0.75(0.47 to 1.21) 0.52 (0.30 to 0.88) p < 0.05 NPC1 544/1157 (47.0%) 26/742(3.5%) 30/718 (4.2%) 3/324 (0.9%) 15/335 (4.5%) 1.25 (0.68 to 2.30) 0.83(0.27 to 2.55) 0.20 (0.04 to 0.98) p < 0.05 NPC1 403/1157 (34.8%)246/742 (33.2%) 290/718 (40.4%) 93/324 (28.7%) 140/335 (41.8%) 1.07(0.81 to 1.42) 0.73 (0.45 to 1.20) 0.56 (0.32 to 0.97) p < 0.05 PEMT560/1157 (48.4%) 72/735 (9.8%) 82/739 (11.1%) 34/305 (11.1%) 31/275(11.3%) 0.42 (0.27 to 0.65) 0.87 (0.42 to 1.82) 0.99 (0.43 to 2.28) p <0.05 PLAU 455/1157 (39.3%) 185/527 (35.1%) 1921499 (38.5%) 19/77 (24.7%)38/78 (48.7%) 0.77 (0.63 to 0.93) 0.86 (0.58 to 1.29) 0.35 (0.16 to0.73) p < 0.05 PON1 190/625 (30.4%) 189/579 (32.6%) 33/144 (22.9%)54/133 (40.6%) 0.77 (0.62 to 0.95) 0.90 (0.59 to 1.37) 0.44 (0.23 to0.81) p < 0.05 PON1 61/560 (10.9%) 14/625 (2.2%) 39/579 (6.7%) 7/144(4.9%) 4/133 (3.0%) 0.83 (0.40 to 1.73) 0.32 (0.09 to 1.18) 1.65 (0.30to 9.06) p < 0.05 PON1 244/560 (43.6%) 13/625 (2.1%) 34/579 (5.9%) 7/144(4.9%) 4/133 (3.0%) 0.95 (0.44 to 2.03) 0.34 (0.09 to 1.33) 1.65 (0.29to 9.33) p < 0.05 SELP 180/560 (32.1%) 60/478 (12.6%) 78/422 (1 8.5%)12/59 (20.3%) 2/47 (4.3%) 0.68 (0.54 to 0.86) 0.63 (0.38 to 1.06) 5.74(1.17 to 28.28) p < 0.05 SELP 254/560 (45.4%) 164/478 (34.3%) 193/422(45.7%) 29/59 (49.2%) 17/47 (36.2%) 0.81 (0.68 to 0.97) 0.62 (0.42 to0.91) 1.71 (0.74 to 3.92) p < 0.05 SELP 204/560 (36.4%) 65/478 (13.6%)78/422 (18.5%) 16/59 (27.1%) 3/47 (6.4%) 0.82 (0.65 to 1.05) 0.69 (0.41to 1.16) 5.45 (1.41 to 21.13) p < 0.05 SERPINA1 14/502 (2.8%) 36/486(7.4%) 2/73 (2.7%) 11/79 (13.9%) 1.03 (0.70 to 1.51) 0.36 (0.15 to 0.86)0.17 (0.03 to 0.92) p < 0.005 SERPINA1 181/410 (44.1%) 6/502 (1.2%)24/486 (4.9%) 1/73 (1.4%) 5/79 (6.3%) 0.87 (0.51 to 1.48) 0.23 (0.07 to0.79) 0.21 (0.02 to 2.10) p < 0.05 TAP1 131/410 (32.0%) 34/414 (8.2%)58/407 (1 4.3%) 2/49 (4.1%) 9/42 (21.4%) 0.85 (0.64 to 1.12) 0.54 (0.29to 1.01) 0.16 (0.03 to 0.82) p < 0.05 TGFB1 19/410 (4.6%) 8/652 (1.2%)29/629 (4.6%) 4/162 (2.5%) 8/162 (4.9%) 1.79 (1.03 to 3.13) 0.26 (0.08to 0.85) 0.49 (0.11 to 2.23) p < 0.0005 TGFB1 1 88/410 (45.9%) 25/652(3.8%) 48/629 (7.6%) 8/162 (4.9%) 12/162 (7.4%) 1.50 (0.96 to 2.34) 0.48(0.20 to 1.16) 0.65 (0.20 to 2.09) p < 0.005 TGFB1 19/410 (4.6%) 156/652(23.9%) 220/629 (35.0%) 60/162 (37.0%) 60/162 (37.0%) 0.91 (0.73 to1.14) 0.58 (0.38 to 0.90) 1.00 (0.56 to 1.77) p < 0.05 TGFB1 11/652(1.7%) 34/629 (5.4%) 5/162 (3.1%) 10/162 (6.2%) 1.95 (1.13 to 3.38) 0.30(0.10 to 0.93) 0.48 (0.12 to 1.99) p < 0.0005 TGFB1 148/410 (36.1%)11/652 (1.7%) 34/629 (5.4%) 5/162 (3.1%) 10/162 (6.2%) 1.90 (1.09 to3.30) 0.30 (0.10 to 0.93) 0.48 (0.12 to 2.00) p < 0.0005 TGFB1 182/652(27.9%) 248/629 (39.4%) 62/162 (38.3%) 70/162 (43.2%) 0.94 (0.76 to1.17) 0.59 (0.39 to 0.90) 0.81 (0.47 to 1.43) p < 0.05 TGFB1 71/462(15.4%) 86/652 (13.2%) 110/629 (17.5%) 27/162 (16.7%) 30/162 (18.5%)1.57 (1.16 to 2.12) 0.72 (0.40 to 1.27) 0.88 (0.41 to 1.87) p < 0.005TGFB1 350/888 (39.4%) 8/652 (1.2%) 16/629 (2.5%) 5/162 (3.1%) 3/162(1.9%) 2.00 (1.14 to 3.51) 0.48 (0.14 to 1.67) 1.69 (0.30 to 9.36) p <0.05 TGFB1 25/652 (3.8%) 35/629 (5.6%) 6/162 (3.7%) 15/162 (9.3%) 1.35(0.88 to 2.07) 0.68 (0.29 to 1.61) 0.38 (0.11 to 1.24) p < 0.05 TLR5266/753 (35.3%) 159/390 (40.8%) 181/371 (48.8%) 5/34 (14.7%) 20/31(64.5%) 0.81 (0.68 to 0.96) 0.72 (0.49 to 1.07) 0.09 (0.03 to 0.32) p <0.005 TLR5 16/753 (2.1%) 106/390 (27.2%) 136/371 (36.7%) 4/34 (11.8%)18/31 (58.1%) 0.86 (0.72 to 1.03) 0.64 (0.42 to 0.98) 0.10 (0.03 to0.35) p < 0.005 TLR5 14/753 (1.9%) 163/390 (41.8%) 188/371 (50.7%) 6/34(17.6%) 21/31 (67.7%) 0.81 (0.69 to 0.97) 0.70 (0.47 to 1.04) 0.10 (0.03to 0.34) p < 0.005 TLR5 205/996 (20.6%) 125/390 (32.1%) 152/371 (41.0%)6/34 (17.6%) 19/31 (61.3%) 0.84 (0.71 to 1.00) 0.68 (0.45 to 1.02) 0.14(0.04 to 0.44) p < 0.05 TNF 19/401 (4.7%) 33/411 (8.0%) 2/56 (3.6%) 5/30(16.7%) 1.11 (0.77 to 1.61) 0.57 (0.25 to 1.30) 0.19 (0.03 to 1.13) p <0.05 TNF 479/996 (48.1%) 31/401 (7.7%) 66/411 (16.1%) 4/56 (7.1%) 7/30(23.3%) 0.80 (0.61 to 1.05) 0.44 (0.24 to 0.81) 0.25 (0.06 to 1.01) p <0.05 TNF 181/996 (18.2%) 156/401 (38.9%) 188/411 (45.7%) 20/56 (35.7%)22/30 (73.3%) 0.79 (0.67 to 0.94) 0.76 (0.51 to 1.12) 0.20 (0.07 to0.56) p < 0.05 TNF 53/915 (5.8%) 158/401 (39.4%) 193/411 (47.0%) 20/56(35.7%) 22/30 (73.3%) 0.79 (0.67 to 0.94) 0.73 (0.50 to 1.08) 0.20 (0.07to 0.56) p < 0.05 ABCC8 61/696 (8.8%) 100/667 (14.8%) 20/197 (102%)24/197 (12.2%) 1.21 (0.84 to 1.73) 0.55 (0.28 to 1.08) 0.81 (0.35 to1.91) p < 0.05 ADAMTS13 30/915 (3.3%) 75/726 (10.3%) 77/667 (11.5%)18/274 (6.6%) 40/259 (15.4%) 0.62 (0.42 to 0.91) 0.88 (0.44 to 1.76)0.38 (0.17 to 0.89) p < 0.05 ADAMTS13 117/1013 (11.5%) 70/726 (9.6%)70/667 (10.5%) 17/274 (6.2%) 39/259 (15.1%) 0.65 (0.44 to 0.96) 0.91(0.45 to 1.83) 0.37 (0.16 to 0.87) p < 0.05 ADAMTS13 20/686 (2.9%)263/726 (36.2%) 277/667 (41.5%) 127/274 (46.4%) 93/259 (35.9%) 0.80(0.63 to 1.03) 0.80 (0.51 to 1.25) 1.54 (0.92 to 2.60) p < 0.005 APOE34/686 (5.0%) 78/749 (10.4%) 81/712 (11.4%) 29/373 (7.8%) 57/390 (14.6%)0.51 (0.32 to 0.80) 0.91 (0.42 to 1.97) 0.49 (0.21 to 1.15) p < 0.05BCL2A1 234/686 (34.1%) 66/579 (11.4%) 66/572 (11.5%) 7/102 (6.9%) 13/95(13.7%) 0.53 (0.39 to 0.72) 0.99 (0.55 to 1.78) 0.46 (0.16 to 1.36) p <0.05 BCL2A1 20/686 (2.9%) 46/579 (7.9%) 42/572 (7.3%) 4/102 (3.9%) 10/95(10.5%) 0.55 (0.38 to 0.78) 1.09 (0.54 to 2.20) 0.35 (0.09 to 1.29) p <0.05 BCL2A1 20/686 (2.9%) 59/579 (10.2%) 54/572 (9.4%) 7/102 (6.9%)11/95 (11.6%) 0.52 (0.38 to 0.71) 1.09 (0.58 to 2.03) 0.56 (0.19 to1.70) p < 0.05 BCL2A1 66/579 (11.4%) 65/572 (11.4%) 7/102 (6.9%) 13/95(13.7%) 0.51 (0.38 to 0.70) 1.00 (0.55 to 1.82) 0.46 (0.16 to 1.36) p <0.05 CCL4 265/686 (38.6%) 9/402 (2.2%) 28/411 (6.8%) 1.28 (0.78 to 2.09)0.31 (0.10 to 0.94) p < 0.005 CCL4 16/402 (4.0%) 39/411 (9.5%) 1.17(0.81 to 1.70) 0.40 (0.17 to 0.91) p < 0.005 CCL4 81/686 (11.8%) 101/402(25.1%) 156/411 (38.0%) 0.87 (0.72 to 1.04) 0.55 (0.36 to 0.83) p < 0.05CCL4 19/686 (2.8%) 10/402 (2.5%) 31/411 (7.5%) 1.30 (0.82 to 2.06) 0.31(0.11 to 0.88) p < 0.005 CCL4 39/686 (5.7%) 9/402 (2.2%) 31/411 (7.5%)1.30 (0.82 to 2.06) 0.28 (0.10 to 0.81) p < 0.005 CCL4 120/402 (29.9%)179/411 (43.6%) 0.86 (0.72 to 1.03) 0.55 (0.37 to 0.82) p < 0.05 CD6492/1070 (46.0%) 220/551 (39.9%) 236/512 (46.1%) 36/115 (31.3%) 42/76(55.3%) 0.81 (0.67 to 0.98) 0.78 (0.53 to 1.14) 0.37 (0.19 to 0.72) p <0.05 CD6 360/1070 (33.6%) 222/551 (40.3%) 145/512 (47.9%) 38/115 (33.0%)43/76 (56.6%) 0.83 (0.69 to 1.00) 0.74 (0.50 to 1.08) 0.38 (0.19 to0.74) p < 0.05 CD6 504/1070 (47.1%) 125/551 (22.7%) 91/512 (17.8%)14/115 (12.2%) 22/76 (28.9%) 1.03 (0.84 to 1.33) 1.36 (0.84 to 2.18)0.34 (0.15 to 0.78) p < 0.005 CD6 411/1070 (38.4%) 42/457 (9.2%) 39/471(8.3%) 3/62 (4.8%) 5/67 (7.5%) 0.52 (0.37 to 0.74) 1.12 (0.56 to 2.25)0.63 (0.13 to 3.02) p < 0.05 CD6 56/457 (12.3%) 52/471 (11.0%) 6/62(9.7%) 7/67 (10.4%) 0.54 (0.40 to 0.73) 1.13 (0.61 to 2.08) 0.92 (0.27to 3.17) p < 0.05 COL11A1 56/1036 (5.4%) 36/417 (8.6%) 70/426 (16.4%)3/73 (4.1%) 8/60 (13.3%) 0.83 (0.63 to 1.09) 0.48 (0.26 to 0.88) 0.28(0.07 to 1.18) p < 0.05 COL11A1 132/1036 (12.7%) 32/417 (7.7%) 66/426(15.5%) 3/73 (4.1%) 7/60 (11.7%) 0.89 (0.67 to 1.20) 0.45 (0.24 to 0.86)0.32 (0.07 to 1.42) p < 0.05 COL11A1 483/1036 (46.6%) 34/417 (8.2%)70/426 (16.4%) 3/73 (4.1%) 8/60 (13.3%) 0.84 (0.64 to 1.11) 0.45 (0.24to 0.84) 0.28 (0.07 to 1.18) p < 0.05 CYP4F2 498/1036 (48.1%) 55/639(8.6%) 77/629 (12.2%) 24/144 (16.7%) 9/125 (7.2%) 0.73 (0.53 to 1.00)0.68 (0.36 to 1.25) 2.58 (1.00 to 6.65) p < 0.05 CYP4F2 61/599 (10.2%)27/639 (4.2%) 14/629 (2.2%) 3/144 (2.1%) 4/125 (3.2%) 0.45 (0.25 to0.79) 1.94 (0.65 to 5.74) 0.64 (0.11 to 3.69) p < 0.005 CYP4F2 76/548(13.9%) 42/639 (6.6%) 30/629 (4.8%) 6/144 (4.2%) 4/125 (3.2%) 0.54 (0.35to 0.84) 1.40 (0.62 to 3.20) 1.32 (0.31 to 5.62) p < 0.05 CYP4F2 73/548(13.3%) 28/639 (4.4%) 17/629 (2.7%) 3/144 (2.1%) 4/125 (3.2%) 0.54 (0.32to 0.90) 1.65 (0.61 to 4.47) 0.64 (0.12 to 3.55) p < 0.05 CYP4F2 235/548(42.9%) 28/639 (4.4%) 17/629 (2.7%) 3/144 (2.1%) 4/125 (3.2%) 0.52 (0.31to 0.87) 1.65 (0.61 to 4.50) 0.64 (0.12 to 3.56) p < 0.05 FCGR2A 57/375(15.2%) 88/783 (11.2%) 79/737 (10.7%) 24/355 (6.8%) 62/377 (16.4%) 0.92(0.59 to 1.44) 1.05 (0.49 to 2.29) 0.37 (0.16 to 0.87) p < 0.005 FCGR2A127/807 (15.7%) 116/783 (14.8%) 134/737 (18.2%) 42/355 (11.8%) 88/377(23.3%) 0.90 (0.61 to 1.32) 0.78 (0.40 to 1.53) 0.44 (0.21 to 0.91) p <0.05 GAPD 88/807 (10.9%) 39/447 (8.7%) 75/451 (16.6%) 4/62 (6.5%) 11/60(18.3%) 0.88 (0.66 to 1.16) 0.48 (0.26 to 0.88) 0.31 (0.09 to 1.11) p <0.05 GAPD 117/807 (14.5%) 36/447 (8.1%) 71/451 (15.7%) 4/62 (6.5%) 9/60(15.0%) 0.87 (0.65 to 1.16) 0.47 (0.25 to 0.87) 0.39 (0.10 to 1.46) p <0.05 GAPD 126/807 (15.6%) 33/447 (7.4%) 70/451 (15.5%) 5/62 (8.1%) 10/60(16.7%) 0.99 (0.74 to 1.33) 0.43 (0.23 to 0.82) 0.44 (0.13 to 1.50) p <0.05 GAPD 29/1059 (2.7%) 34/447 (7.6%) 64/451 (14.2%) 3/62 (4.8%) 9/60(15.0%) 0.89 (0.66 to 1.19) 0.50 (0.26 to 0.94) 0.29 (0.07 to 1.21) p <0.05 GAPD 55/1059 (5.2%) 39/447 (8.7%) 74/451 (16.4%) 4/62 (6.5%) 11/60(18.3%) 0.86 (0.64 to 1.14) 0.49 (0.27 to 0.89) 0.31 (0.08 to 1.11) p <0.05 IL12A 355/1059 (33.5%) 68/761 (8.9%) 72/718 (10.0%) 20/277 (7.2%)19/267 (7.1%) 0.37 (0.22 to 0.61) 0.88 (0.38 to 2.06) 1.02 (0.37 to2.80) p < 0.05 IL12A 33/1059 (3.1%) 123/761 (16.2%) 133/718 (18.5%)41/277 (14.8%) 40/267 (15.0%) 0.40 (0.28 to 0.57) 0.85 (0.46 to 1.58)0.99 (0.47 to 2.05) p < 0.005 IL9 33/1059 (3.1%) 21/348 (6.0%) 49/302(16.2%) 2/33 (6.1%) 5/24 (20.8%) 0.81 (0.63 to 1.04) 0.33 (0.17 to 0.65)0.25 (0.04 to 1.45) p < 0.05 IL9 20/348 (5.7%) 49/302 (16.2%) 2/33(6.1%) 5/24 (20.8%) 0.83 (0.64 to 1.07) 0.31 (0.16 to 0.62) 0.25 (0.04to 1.46) p < 0.005 IL9 401/1059 (37.9%) 20/348 (5.7%) 45/302 (14.9%)2/33 (6.1%) 5/24 (20.8%) 0.83 (0.64 to 1.09) 0.35 (0.17 to 0.70) 0.25(0.04 to 1.46) p < 0.05 IL9 21/348 (6.0%) 48/302 (15.9%) 2/33 (6.1%)5/24 (20.8%) 0.80 (0.62 to 1.03) 0.34 (0.17 to 0.66) 0.25 (0.04 to 1.46)p < 0.05 KLK14 415/888 (46.7%) 67/657 (10.2%) 89/629 (14.1%) 11/160(6.9%) 35/156 (22.4%) 0.84 (0.60 to 1.18) 0.69 (0.37 to 1.29) 0.26 (0.10to 0.62) p < 0.05 KLK14 425/888 (47.9%) 62/657 (9.4%) 81/629 (12.9%)10/160 (6.3%) 33/156 (21.2%) 0.82 (0.58 to 1.16) 0.70 (0.37 to 1.34)0.25 (0.10 to 0.62) p < 0.05 KLK14 181/888 (20.4%) 47/657 (7.2%) 58/629(9.2%) 7/160 (4.4%) 25/156 (16.0%) 0.84 (0.56 to 1.25) 0.76 (0.36 to1.59) 0.24 (0.08 to 0.70) p < 0.05 KLK14 97/935 (10.4%) 41/657 (6.2%)79/629 (12.6%) 9/160 (5.6%) 16/156 (9.6%) 1.04 (0.71 to 1.53) 0.46 (0.23to 0.95) 0.56 (0.20 to 1.60) p < 0.05 KLK14 126/935 (13.5%) 65/657(9.9%) 79/629 (12.6%) 9/160 (5.6%) 32/156 (20.5%) 0.88 (0.62 to 1.25)0.76 (0.40 to 1.47) 0.23 (0.09 to 0.60) p < 0.05 KLK14 122/966 (12.6%)60/657 (9.1%) 74/629 (11.8%) 10/160 (6.3%) 32/156 (20.5%) 0.81 (0.57 to1.16) 0.75 (0.39 to 1.46) 0.26 (0.10 to 0.66) p < 0.05 KLK14 103/966(10.7%) 66/657 (10.0%) 88/629 (14.0%) 11/160 (6.9%) 35/156 (22.4%) 0.82(0.58 to 1.16) 0.69 (0.36 to 1.30) 0.26 (0.10 to 0.63) p < 0.05 LAMA5120/966 (12.4%) 36/664 (5.4%) 64/629 (10.0%) 9/221 (4.1%) 23/215 (10.7%)1.03 (0.69 to 1.53) 0.52 (0.24 to 1.10) 0.35 (0.13 to 0.97) p < 0.05LAMA5 100/720 (13.9%) 49/664 (7.4%) 84/629 (13.1%) 12/221 (5.4%) 27/215(12.6%) 0.97 (0.69 to 1.38) 0.53 (0.27 to 1.03) 0.40 (0.16 to 0.98) p <0.05 LAMA5 39/720 (5.4%) 51/664 (7.7%) 90/629 (14.1%) 17/221 (7.7%)32/215 (14.9%) 0.89 (0.64 to 1.25) 0.51 (0.27 to 0.96) 0.48 (0.21 to1.08) p < 0.05 MARK3 60/720 (8.3%) 63/906 (7.0%) 100/879 (11.4%) 1.03(0.65 to 1.65) 0.58 (0.26 to 1.31) p < 0.05 MARK3 43/720 (6.0%) 82/906(9.1%) 125/879 (14.2%) 1.00 (0.68 to 1.47) 0.60 (0.30 to 1.19) p < 0.05MJD 43/720 (6.0%) 66/547 (12.1%) 61/506 (12.1%) 10/89 (11.2%) 15/100(15.0%) 0.54 (0.40 to 0.74) 1.00 (0.55 to 1.83) 0.72 (0.27 to 1.91) p <0.05 MJD 62/547 (11.3%) 56/506 (11.1%) 10/89 (11.2%) 13/100 (13.0%) 0.53(0.38 to 0.72) 1.03 (0.55 to 1.91) 0.85 (0.31 to 2.31) p < 0.05 MJD45/363 (12.4%) 61/547 (11.2%) 50/506 (9.9%) 10/89 (11.2%) 12/100 (12.0%)0.51 (0.37 to 0.71) 1.14 (0.61 to 2.16) 0.93 (0.33 to 2.58) p < 0.05 MJD64/363 (17.6%) 65/547 (11.9%) 61/506 (12.1%) 10/89 (11.2%) 14/100(14.0%) 0.53 (0.39 to 0.72) 0.98 (0.54 to 1.80) 0.78 (0.29 to 2.09) p <0.05 MJD 96/547 (17.6%) 79/506 (15.6%) 9/89 (10.1%) 18/100 (18.0%) 0.70(0.54 to 0.90) 1.15 (0.69 to 1.93) 0.51 (0.20 to 1.32) p < 0.05 MMP27114/932 (12.2%) 68/746 (9.1%) 81/715 (11.3%) 27/331 (8.2%) 46/310(14.8%) 1.24 (0.78 to 1.97) 0.79 (0.35 to 1.78) 0.51 (0.21 to 1.25) p <0.05 NID2 108/932 (11.6%) 23/561 (4.1%) 44/549 (8.0%) 2/115 (1.7%) 8/88(9.1%) 1.01 (0.66 to 1.53) 0.49 (0.21 to 1.13) 0.18 (0.03 to 0.98) p <0.05 PECAM1 98/932 (10.5%) 22/716 (3.1%) 22/679 (3.2%) 3/318 (0.9%)19/351 (5.4%) 0.37 (0.15 to 0.91) 0.95 (0.22 to 4.14) 0.17 (0.03 to1.03) p < 0.05 PLAB 103/932 (11.1%) 44/551 (8.0%) 87/542 (16.1%) 5/87(5.7%) 11/98 (11.2%) 0.85 (0.64 to 1.14) 0.45 (0.25 to 0.82) 0.48 (0.15to 1.59) p < 0.05 PLAB 113/932 (12.1%) 41/551 (7.4%) 81/542 (14.9%) 5/87(5.7%) 11/98 (11.2%) 0.85 (0.63 to 1.14) 0.46 (0.25 to 0.85) 0.48 (0.15to 1.59) p < 0.05 PLAB 56/459 (12.2%) 28/551 (5.1%) 65/542 (12.0%) 5/87(5.7%) 6/98 (6.1%) 0.94 (0.66 to 1.32) 0.39 (0.19 to 0.80) 0.93 (0.24 to3.57) p < 0.05 PLAB 109/459 (23.7%) 42/551 (7.6%) 81/542 (14.9%) 6/87(6.9%) 8/98 (8.2%) 0.89 (0.66 to 1.21) 0.47 (0.25 to 0.87) 0.83 (0.25 to2.77) p < 0.05 PLAB 39/551 (7.1%) 78/542 (14.4%) 5/87 (5.7%) 10/98(10.2%) 0.88 (0.65 to 1.20) 0.45 (0.24 to 0.85) 0.54 (0.16 to 1.81) p <0.05 PLAB 153/1151 (13.3%) 44/551 (8.0%) 86/542 (15.9%) 5/87 (5.7%)11/98 (11.2%) 0.83 (0.62 to 1.11) 0.46 (0.25 to 0.84) 0.48 (0.15 to1.59) p < 0.05 PTPN21 141/1151 (12.3%) 26/646 (4.0%) 51/673 (7.6%) 6/177(3.4%) 16/162 (9.9%) 1.19 (0.73 to 1.95) 0.51 (0.20 to 1.29) 0.32 (0.09to 1.11) p < 0.05 PTPN21 133/1151 (11.6%) 26/642 (4.0%) 51/673 (7.6%)6/172 (3.5%) 15/155 (9.7%) 1.10 (0.68 to 1.79) 0.51 (0.21 to 1.28) 0.34(0.10 to 1.17) p < 0.05 QSCN6 152/1151 (13.2%) 41/376 (10.9%) 39/405(9.6%) 5/38 (13.2%) 5/42 (11.9%) 0.53 (0.38 to 0.73) 1.15 (0.58 to 2.27)1.12 (0.27 to 4.62) p < 0.05 SERPINA1 81/685 (11.8%) 38/420 (9.0%)43/413 (10.4%) 22/298 (7.4%) 18/277 (6.5%) 0.47 (0.32 to 0.68) 0.86(0.41 to 1.80) 1.15 (0.48 to 2.74) p < 0.05 SERPINB6 79/685 (11.5%)198/612 (32.4%) 227/603 (37.6%) 41/138 (29.7%) 69/138 (50.0%) 0.84 (0.68to 1.03) 0.79 (0.53 to 1.19) 0.42 (0.23 to 0.77) p < 0.05 SN 57/685(8.3%) 60/786 (7.6%) 66/745 (8.9%) 9/326 (2.8%) 34/337 (10.1%) 0.78(0.48 to 1.26) 0.85 (0.37 to 1.96) 0.25 (0.09 to 0.73) p < 0.05 SN57/685 (8.3%) 75/786 (9.5%) 76/745 (10.2%) 32/326 (9.8%) 29/337 (8.6%)0.48 (0.30 to 0.77) 0.93 (0.42 to 2.05) 1.16 (0.47 to 2.81) p < 0.05 SN73/685 (10.7%) 85/786 (10.8%) 89/745 (11.9%) 15/326 (4.6%) 43/337(12.8%) 0.70 (0.45 to 1.08) 0.89 (0.42 to 1.90) 0.33 (0.13 to 0.82) p <0.05 SN 75/685 (10.9%) 117/786 (14.9%) 135/745 (18.1%) 49/326 (15.0%)53/337 (15.7%) 0.45 (0.31 to 0.65) 0.79 (0.42 to 1.49) 0.95 (0.47 to1.93) p < 0.05 SN 80/685 (11.7%) 240/786 (30.5%) 243/745 (32.6%) 92/326(28.2%) 114/337 (33.8%) 0.57 (0.42 to 0.77) 0.91 (0.54 to 1.52) 0.77(0.43 to 1.36) p < 0.05 TGFB1 53/616 (8.6%) 14/712 (2.0%) 32/678 (4.7%)5/244 (2.0%) 12/254 (4.7%) 2.23 (1.15 to 4.34) 0.40 (0.11 to 1.43) 0.42(0.09 to 1.93) p < 0.005 TGFB1 71/616 (11.5%) 33/712 (4.6%) 52/678(7.7%) 9/244 (3.7%) 20/254 (7.9%) 1.87 (1.10 to 3.19) 0.59 (0.22 to1.55) 0.45 (0.14 to 1.46) p < 0.005 TGFB1 82/616 (13.3%) 178/712 (25.0%)243/678 (35.8%) 81/244 (33.2%) 86/254 (33.9%) 0.93 (0.73 to 1.20) 0.60(0.38 to 0.95) 0.97 (0.56 to 1.67) p < 0.05 TGFB1 37/566 (6.5%) 18/712(2.5%) 36/678 (5.3%) 6/244 (2.5%) 15/254 (5.9%) 2.39 (1.24 to 4.63) 0.46(0.14 to 1.58) 0.40 (0.09 to 1.71) p < 0.0005 TGFB1 56/566 (9.9%) 17/712(2.4%) 36/678 (5.3%) 6/244 (2.5%) 15/254 (5.9%) 2.39 (1.24 to 4.63) 0.44(0.13 to 1.49) 0.40 (0.09 to 1.71) p < 0.0005 TLR6 123/828 (14.9%)13/692 (1.9%) 24/689 (3.5%) 17/276 (6.2%) 5/253 (2.0%) 0.61 (0.33 to1.12) 0.53 (0.17 to 1.69) 3.26 (0.82 to 12.92) p < 0.05 TLR6 118/828(14.3%) 17/692 (2.5%) 29/689 (4.2%) 19/276 (6.9%) 5/253 (2.0%) 0.60(0.33 to 1.08) 0.57 (0.19 to 1.71) 3.67 (0.95 to 14.17) p < 0.005 TLR6113/828 (13.6%) 17/692 (2.5%) 29/689 (4.2%) 18/276 (6.5%) 5/253 (2.0%)0.60 (0.33 to 1.08) 0.57 (0.19 to 1.71) 3.46 (0.89 to 13.42) p < 0.05VEGF 122/828 (14.7%) 9/372 (2.4%) 27/384 (7.0%) 1/51 (2.0%) 2/34 (5.9%)1.29 (0.82 to 2.03) 0.33 (0.11 to 0.94) 0.32 (0.03 to 4.09) p < 0.05VEGF 161/828 (19.4%) 9/372 (2.4%) 27/384 (7.0%) 1/51 (2.0%) 2/34 (5.9%)1.26 (0.80 to 1.99) 0.33 (0.11 to 0.95) 0.32 (0.03 to 4.09 p < 0.05*Results of the Overall Score Test (chi-square test) for the logisticregression model in which the qualitative phenotype is a function of SNPgenotype, treatment group, and the interaction between SNP genotype andtreatment group. **Results of the chi-square test of the interactionbetween SNP genotype and treatment group (based on the logisticregression model).

TABLE 9 RMI_Logistic Regression Endpoint Public Marker Genotype/modeStrata Confounder P risk est^(a) RMI (fatal MI, A2M hCV517658 Het (CT)All statin, hx_smoke* 0.026 confirmed non-fatal MI) RMI (fatal MI, ENPP1hCV1207994 Het (CA) All statin 0.0706 confirmed non-fatal MI) RMI (fatalMI, IGF1R hCV8722981 Het (TC) All statin 0.0039 confirmed non-fatal MI)RMI (fatal MI, IRF3 hCV7798230 Rec (GG) All statin 0.0071 confirmednon-fatal MI) RMI (fatal MI, LRP2 hCV16165996 Rec (TT) All statin 0.0324confirmed non-fatal MI) RMI (fatal MI, MC3R hCV22274632 Het (CA) Allstatin, hx_smoke* 0.0565 confirmed non-fatal MI) RMI (fatal MI, MC3RhCV25640926 Het (GA) All statin, hx_smoke* 0.0264 confirmed non-fatalMI) RMI (fatal MI, MC3R hCV9485713 Het (CT) All statin, hx_smoke* 0.0225confirmed non-fatal MI) RMI_Logistic Regression Endpoint RR^(b) 95%CI^(c) case^(d) Case AF(%)^(e) control^(f) Control AF (%)^(g) RMI (fatalMI, 1.34 1.04-1.71 130 51.8 1137 44.8 confirmed non-fatal MI) RMI (fatalMI, 1.28 0.98-1.65 73 28.9 616 24.2 confirmed non-fatal MI) RMI (fatalMI, 2.01 1.26-3.06 17 6.7 80 3.1 confirmed non-fatal MI) RMI (fatal MI,1.61 1.14-2.23 42 16.5 257 10.1 confirmed non-fatal MI) RMI (fatal MI,0.45 0.21-0.93 7 2.8 160 6.3 confirmed non-fatal MI) RMI (fatal MI, 1.340.99-1.78 50 19.7 397 15.6 confirmed non-fatal MI) RMI (fatal MI, 1.41.04-1.85 51 20.1 389 15.2 confirmed non-fatal MI) RMI (fatal MI, 1.411.05-1.87 51 20.2 388 15.2 confirmed non-fatal MI) *History of smoking^(a)Significance of risk estimated by Wald test ^(b)Relative risk^(c)95% confidence interval for relative risk ^(d)Number of patients(with the corresponding genotype or mode) developed recurrent MI during5 years of follow up ^(e)The allele frequency of patients (with thecorresponding genotype or mode) developed recurrent MI during 6 years offollow up ^(f)Number of patients (with the corresponding genotype ormode) had MI ^(g)The allele frequency of patients (with thecorresponding genotype or mode) had MI RMI Replication Between CAREandPreCARE Sample Sets Analysis 1 of CARE samples Endpoint Pubic MarkerGenotype/mode Strata P risk est^(a) OR^(b) 95% CI^(c) case^(d) CaseAF(%)^(e) RMI (fatal MI, FABP2 hCV761961 Dom (TC + TT) AGE_T1 0.01 0.500.3-0.9 19 40.8 confirmed non-fatal MI) RMI (fatal MI, HLA-DPB1hCV8851080 Rec (GG) AGE_T3 0.037 2.70 1.1-6.7 10 11.1 confirmednon-fatal MI) RMI (fatal MI, IL12RB1 hCV795442 Allelic (G) BMI > 30.50.06 0.60 0.4-1.0 29 25.0 confirmed non-fatal MI) RMI (fatal MI, KDRhCV16192174 Alelic (A) HYP_Y 0.03 1.80 1.1-3.3 28 23.5 confirmednon-fatal MI) RMI (fatal MI, KLKB1 hCV22272267 Dom (GA + AA) HYP_Y 0.0251.80 1.1-3.1 96 82.1 confirmed non-fatal MI) RMI (fatal MI, MMP7hCV3210838 Allelic (T) AGE_T1 0.029 0.60 0.3-1.0 21 13.8 confirmednon-fatal MI) RMI (fatal MI, WRN hCV3020386 Rec (TT) AGE_T1 0.06 1.81.0-3.4 20 26.3 confirmed non-fatal MI) RMI (fatal MI, LRP2 hCV16165996Rec (TT) All 0.015 0.30 0.1-0.9 7 2.8 confirmed non-fatal MI) RMI (fatalMI, LRP8 hCV190754 Het (TC)/Dom APOE4 0.1 1.80 0.9-3.6 28 confirmednon-fatal MI) (TC + TT) allele RMI (fatal MI, LRP8 hCV190754 Het(TC)/Dom APOE4 not 1.00 0.7-1.4 75 confirmed non-fatal MI) (TC + TT) RMI(fatal MI, KDR hCV16192174 Dom (AA + AG) APOE4 0.0011 2.80 1.4-5.4 18confirmed non-fatal MI) allele RMI (fatal MI, KDR hCV16192174 Dom (AA +AG) APOE4 not 0.70 0.4-1.2 25 confirmed non-fatal MI) RMI (fatal MI, KDRhCV16192174 Dom (AA + AG) confirmed non-fatal MI) RMI (fatal MI, KDRhCV16192174 Dom (AA + AG) confirmed non-fatal MI) RMI ReplicationBetween CAREand PreCARE Sample Sets Analysis 1 of CARE samples Analysis2 of CARE Samples Endpoint control^(f) Control AF(%)^(g) Strata P riskest^(a) OR^(b) 95% CI^(c) case^(d) Case AF(%)^(e) control^(f) ControlAF(%)^(g) RMI (fatal MI, 110 25.2 AGE_T1 0.01 0.5 0.3-0.9 21 26.6 18741.7 confirmed non-fatal MI) RMI (fatal MI, 11 4.4 AGE_T3 0.039 1.91.0-3.6 19 10.7 25 5.8 confirmed non-fatal MI) RMI (fatal MI, 104 34.7BMI > 30.5 0.006 0.5 0.4-0.8 33 23.2 182 35.7 confirmed non-fatal MI)RMI (fatal MI, 45 14.4 HYP_Y 0.03 1.7 1.0-2.7 4 2.4 2 0.4 confirmednon-fatal MI) RMI (fatal MI, 223 71.3 HYP_Y 0.034 1.3 1.0-1.7 180 53.6500 46.9 confirmed non-fatal MI) RMI (fatal MI, 117 21.8 AGE_T1 0.0330.6 0.4-1.0 23 14.6 197 22.0 confirmed non-fatal MI) RMI (fatal MI, 4316.3 AGE_T1 0.018 1.9 1.1-3.1 30 38.0 110 24.7 confirmed non-fatal MI)RMI (fatal MI, 65 6.2 All 0.002 0.3 0.1-0.7 11 2.8 92 7.0 confirmednon-fatal MI) RMI (fatal MI, 124 APOE4 allele 0.1 1.5 0.9-2.3 60 128confirmed non-fatal MI) RMI (fatal MI, 389 APOE4 not 0.98 0.7-1.4 154391 confirmed non-fatal MI) RMI (fatal MI, 51 APOE4 allele 0.2 1.50.9-2.6 26 43 confirmed non-fatal MI) RMI (fatal MI, 167 APOE4 not 1.0 0.7-1.37 confirmed non-fatal MI) RMI (fatal MI, APOE4/2 0.0048 16.61.28-158  confirmed non-fatal MI) RMI (fatal MI, APOE4 not 1.0  0.8-1.42confirmed non-fatal MI) ^(a)Significance of risk estimated by Wald test^(b)Odds ratio ^(c)95% confidence interval for odds ratio ^(d)Number ofpatents (with the corresponding genotype or mode) developed recurrent MIduring 5 years of follow up ^(e)The allele frequency of patents (withthe corresponding genotype or mode) developed recurrent MI during 6years of follow up ^(f)Number of patients (with the correspondinggenotype or mode) had MI ^(g)The allele frequency of patients (with thecorresponding genotype or mode) had MI AGE_T1 indicate that Age < 55AGE_T13 indicate that age >= 64 |HYP_Y indicate that patients hadhistory of hypertension Stroke Replication Between CAREand PreCARESample Sets Analysis 1 of CARE Samples Endpoint Public Marker Genotype/mode Strata P risk est^(a) OR^(b) 95% CI^(c) case^(d) Case AF(%)^(e)Stroke ACAT2 hCV1361979 Dom (AA + GA)/ male 0.015 1.7 1.1-2.7 89 75.42Allelic (G) Stroke APOA4 hCV11482766 Rec(CC) all 0.016 3.5 1.4-9.1 64.23 Stroke HTR2A hCV11696920 Rec(AA) all 0.06 5.8  1.9-18.1 5 3.52Stroke ICAM1 hCV8726331 Rec(AA) all 0.1 3 1.2-9.3 5 3.52 Stroke ICAM1hCV8726331 Rec(AA) male 0.01 4.8  1.6-14.3 5 4.17 Stroke KCNMB1hCV3026206 Het(GC) male 0.019 1.7 1.1-2.7 29 24.58 Stroke ReplicationBetween CAREand PreCARE Sample Sets Analysis 1 of CARE samples Analysis2 of CARE Samples Endpoint control^(f) Control AF(%)^(g) Strata P riskest^(a) OR^(b) 95% CI^(c) case^(d) Case AF(%)^(e) control^(f) ControlAF(%)^(g) Stroke 715 64.18 male 0.013 1.5 1.1-2.2 73 53.68 926 42.71Stroke 16 1.24 all 0.05 3.3 1.1-9.8 4 5 20 1.59 Stroke 8 0.62 all 0.0384.9  1.3-18.0 3 3.75 10 0.79 Stroke 14 1.09 all 0.04 2.6  0.9-10.6 33.75 16 1.27 Stroke 10 0.9 male 0.06 3.8  1.1-13.8 3 4.41 13 1.19 Stroke176 15.81 male 0.074 1.7 1.0-2.9 18 26.47 193 17.69 ^(a)Significance ofrisk estimated by Wald test ^(b)Odds ratio ^(c)95% confidence intervalfor odds ratio ^(d)Number of patients (with the corresponding genotypeor mode) developed recurrent MI during 5 years of follow up ^(e)Theallele frequency of patients (with the corresponding genotype or mode)developed recurrent MI during 6 years of follow up ^(f)Number ofpatients (with the corresponding genotype or mode) had MI ^(g)The allelefrequency of patients (with the corresponding genotype or mode) had MI

TABLE 10 Risk of cardiovascular disease events associated withPravastatin by genotypes Case Y Control Y Gene PRIMER ALLELE PRIMERALLELE symbol hCV Nucleotide Freq* Nucleotide Freq** Stratum Groupptrend^(a) N aff^(b) N unaf^(fc) RR^(d) RR 95% CI^(e) P_(risk est) ^(f)P_(int) ^(g) Covars^(h) ATF6 hCV25631989 0.04 0.08 Placebo hom(TT) vs.ref (CC) 1 5 1.49 (0.25-9.00) 0.6624 0.0069 none het(TC) vs. ref (CC) 9185 0.42 (0.22-0.80) 0.0089 ref (CC) 128 1018 1.00 Statin hom(TT) vs.ref (CC) 0 11 NA het(TC) vs. ref (CC) 24 189 1.53 (0.99-2.34) 0.0535 ref(CC) 85 1066 1.00 Maj Hom(CC) Statin 85 1066 0.66 (0.51-0.86) 0.0019Placebo 128 1018 1.00 Het(TC) Statin 24 189 2.43 (1.165.10) 0.0189Placebo 9 185 1.00 Min Hom(TT) Statin 0 11 NA Placebo 1 5 1.00 LAMA2hCV16047108 0.06 0.07 Placebo hom(GG) vs. ref (AA) 0 7 NA 0.0057 nonehet(GA) vs. ref (AA) 17 147 0.98 (0.61-1.58) 0.9257 ref (AA) 128 10791.00 Statin hom(GG) vs. ref (AA) 2 4 4.97 (1.57-15.70) 0.0063 het(GA)vs. ref (AA) 22 140 2.02 (1.30-3.14) 0.0017 ref (AA) 84 1168 1.00 MajHom(AA) Statin 84 1168 0.63 (0.49-0.82) 0.0007 Placebo 128 1079 1.00Het(GA) Statin 22 140 1.31 (0.72-2.37) 0.3732 Placebo 17 147 1.00 MinHom(GG) Statin 2 4 NA Placebo 0 7 1.00 ITGA9 hCV25644901 0.08 0.04Placebo dom(GA + GG)vs. ref(AA) 24 105 1.92 (1.29-2.86) 0.0013 0.0093none ref (AA) 121 1129 1.00 Statin dom(GA + GG)vs. ref(AA) 6 123 0.58(0.26-1.31) 0.1904 ref (AA) 103 1192 1.00 Maj Hom(AA) Statin 103 11920.82 (0.64-1.06) 0.1251 Placebo 121 1129 1.00 Dom (GA + GG) Statin 6 1230.25 (0.11-0.59) 0.0016 Placebo 24 105 1.00 LAMA5 hCV25629492 0.38 0.36Placebo hom (GG) vs. ref (AA) 0.3885 25 172 1.26 (0.81-1.95) 0.30860.0173 none het(GA) vs. ref(AA) 61 532 1.02 (0.73-1.43) 0.9170 ref(AA)59 525 1.00 Statin hom(GG) vs. ref (AA) 0.0193 13 193 0.64 (0.36-1.14)0.1306 het(GA) vs. ref(AA) 36 595 0.58 (0.39-0.86) 0.0074 ref(AA) 57 5201.00 Maj Hom(AA) Statin 57 520 0.98 (0.69-1.38) 0.8972 Placebo 59 5251.00 Het(GA) Statin 36 595 0.55 (0.37-0.82) 0.0036 Placebo 61 532 1.00Min Hom(GG) Statin 13 193 0.50 (0.26-0.94) 0.0327 Placebo 25 172 1.00KLK14 hCV16044337 0.62 0.69 Placebo hom(AA) vs. ref(GG) 0.0096 23 1171.87 (1.19-2.92) 0.0063 0.0188 none het(GA) vs. ref(GG) 64 521 1.24(0.89-1.75) 0.2073 ref(GG) 57 591 1.00 Statin hom(AA) vs. ref(GG) 0.33716 128 0.56 (0.25-1.28) 0.1678 het(GA) vs. ref(GG) 50 570 1.01(0.69-1.46) 0.9629 ref(GG) 53 610 1.00 Maj Hom(GG) Statin 53 610 0.91(0.64-1.30) 0.6005 Placebo 57 591 1.00 Het(GA) Statin 50 570 0.74(0.52-1.05) 0.0897 Placebo 64 521 1.00 Min Hom(AA) Statin 6 128 0.27(0.11-0.65) 0.0033 Placebo 23 117 1.00 GAPD hCV8921288 0.75 0.81 Placebohom(CC) vs. ref(AA) 0.0239 7 51 1.38 (0.67-2.86) 0.3819 0.0209 nonehet(AC) vs. ref(AA) 55 363 1.51 (1.09-2.09) 0.0138 ref(AA) 76 795 1.00Statin hom(CC) vs. ref(AA) 0.1309 4 54 0.81 (0.31-2.13) 0.6634 het(AC)vs. ref(AA) 27 391 0.76 (0.50-1.15) 0.1924 ref(AA) 78 834 1.00 MajHom(AA) Statin 78 834 0.98 (0.72-1.33) 0.8966 Placebo 76 795 1.00Het(AC) Statin 27 391 0.49 (0.32-0.76) 0.0015 Placebo 55 363 1.00 MinHom(CC) Statin 4 54 0.57 (0.18-1.85) 0.3499 Placebo 7 51 1.00 CD6hCV25922320 0.82 0.78 Placebo hom(AA) vs. ref(GG) 0.0815 4 60 0.53(0.20-1.38) 0.1911 0.0140 HX_ het(GA) vs. ref(GG) 43 415 0.80(0.57-1.12) 0.1872 SMOKE_1 ref(GG) 98 756 1.00 Statin hom(AA) vs.ref(GG) 0.0860 3 57 0.79 (0.25-2.43) 0.6753 het(GA) vs. ref(GG) 46 3951.65 (1.14-2.38) 0.0077 ref(GG) 59 861 1.00 Maj Hom(GG) Statin 59 8610.55 (0.40-0.74) 0.0001 Placebo 98 756 1.00 Het(GA) Statin 46 395 1.13(0.76-1.68) 0.5393 Placebo 43 415 1.00 Min Hom(AA) Statin 3 57 0.82(0.19-3.49) 0.7846 Placebo 4 60 1.00 SLC18A1 hCV2715953 0.88 0.92Placebo hom(CC) vs. ref(GG) 0.0714 4 17 1.92 (0.78-4.71) 0.1560 0.0274none het(GC) vs. ref (GG) 26 175 1.30 (0.87-1.94) 0.1950 ref(GG) 1151042 1.00 Statin hom(CC) vs. ref(GG) 0.1356 0 12 0.9995 het(GC) vs. ref(GG) 14 229 0.72 (0.42-1.23) 0.2295 ref(GG) 93 1063 1.00 Maj Hom(GG)Statin 93 1063 0.81 (0.62-1.05) 0.1121 Placebo 115 1042 1.00 Het(GC)Statin 14 229 0.45 (0.24-0.83) 0.0109 Placebo 26 175 1.00 Min Hom(CC)Statin 0 12 Placebo 4 17 1.00 PTPRJ hCV8895373 0.86 0.82 Placebohom(AA)vs. ref(GG) 0.1002 2 40 0.42 (0.11-1.65) 0.2156 0.0209 nonehet(GA) vs. ref(GG) 36 360 0.81 (0.56-1.15) 0.2400 ref(GG) 106 834 1.00Statin hom(AA)vs. ref(GG) 0.1045 3 36 1.14 (0.37-3.46) 0.8192 het(GA)vs. ref(GG) 41 382 1.43 (0.99-2.08) 0.0585 ref(GG) 65 897 1.00 MajHom(GG) Statin 65 897 0.60 (0.45-0.81) 0.0007 Placebo 106 834 1.00Het(GA) Statin 41 382 1.07 (0.70-1.63) 0.7862 Placebo 36 360 1.00 MinHom(AA) Statin 3 36 1.62 (0.28-9.16) 0.5881 Placebo 2 40 1.00 IL4RhCV2769554 0.38 0.46 Placebo hom(GG) vs. ref(AA) 0.0207 16 279 0.47(0.27-0.81) 0.0067 0.0297 none het(GA) vs. ref(AA) 79 569 1.06(0.76-1.48) 0.7287 ref (AA) 50 385 1.00 Statin hom(GG) vs. ref(AA)0.3773 27 292 1.26 (0.75-2.10) 0.3819 het(GA) vs. ref(AA) 55 646 1.17(0.75-1.82) 0.4995 ref (AA) 27 374 1.00 Maj Hom(AA) Statin 27 374 0.59(0.37-0.92) 0.0193 Placebo 50 385 1.00 Het(GA) Statin 55 646 0.64(0.46-0.89) 0.0083 Placebo 79 569 1.00 Min Hom(GG) Statin 27 292 1.56(0.86-2.84) 0.1445 Placebo 16 279 1.00 F7 hCV783184 0.09 0.12 Placebohom(TT) vs. ref(GG) 0.1044 1 21 0.41 (0.06-2.79) 0.3616 0.0373 none het(TG) vs. ref(GG) 23 255 0.74 (0.49-1.14) 0.1737 ref(GG) 120 959 1.00Statin hom(TT) vs. ref(GG) 0.1895 2 15 1.65 (0.44-6.17) 0.4568 het (TG)vs. ref(GG) 27 270 1.28 0.84-1.94) 0.2543 ref(GG) 79 1029 1.00 MajHom(GG) Statin 79 1029 0.64 (0.49-0.84) 0.0013 Placebo 120 959 1.00Het(TG) Statin 27 270 1.10 (0.65-1.87) 0.7282 Placebo 23 255 1.00 MinHom(TT) Statin 2 15 2.59 (0.26-26.22) 0.4208 Placebo 1 21 1.00 EDG3hCV25610470 0.95 0.96 Placebo hom(AA) vs. ref(GG) 0.5799 0 4 0.0645 HX_het(GA) vs. ref(GG) 13 83 1.27 (0.75-2.15) 0.3834 SMOKE ref(GG) 131 11481.00 Statin hom(AA) vs. ref(GG) 0.0745 0 3 het(GA) vs. ref(GG) 3 1010.37 (0.12-1.13) 0.0818 ref(GG) 105 1205 1.00 Maj Hom(GG) Statin 1051205 0.77 (0.61-0.98) 0.0390 Placebo 131 1148 1.00 Het(GA) Statin 3 1010.22 (0.07-0.76) 0.0165 Placebo 13 83 1.00 Min Hom(AA) Statin 0 3 1.10Placebo 0 4 1.00 FCAR hCV7841642 0.90 0.93 Placebo hom (AA)vs. ref(GG)0.0687 1 11 0.85 (0.13-5.59) 0.8656 0.0463 none het(GA) vs. ref(GG) 28159 1.53 (1.05-2.24) 0.0302 ref(GG) 116 1067 1.00 Statin hom (AA)vs.ref(GG) 0.2107 1 8 1.38 (0.22-8.83) 0.7350 het(GA) vs. ref(GG) 9 1780.60 (0.31-1.16) 0.1283 ref(GG) 99 1129 1.00 Maj Hom(GG) Statin 99 11290.82 (0.64-1.06) 0.1339 Placebo 116 1067 1.00 Het(GA) Statin 9 178 0.32(0.16-0.66) 0.0021 Placebo 28 159 1.00 Min Hom(AA) Statin 1 8 1.33(0.10-18.57) 0.8305 Placebo 1 11 1.00 PLAB hCV7494810 0.27 0.25 Placebohom(GG)vs. ref(CC) 0.2988 7 83 0.85 (0.41-1.80) 0.6778 0.0326 HX_het(GC) vs. ref(CC) 65 442 1.39 (1.01-1.90) 0.0408 SMOKE ref(CC) 73 7091.00 Statin hom(GG) vs. ref(CC) 0.0605 5 78 0.68 (0.28-1.63) 0.3889het(GC) vs. ref(CC) 31 491 0.67 (0.45-1.01) 0.0534 ref(CC) 72 744 1.00Maj Hom(CC) Statin 72 744 0.94 (0.69-1.29) 0.7177 Placebo 73 709 1.00Het(GC) Statin 31 491 0.46 (0.30-0.69) 0.0002 Placebo 65 442 1.00 MinHom(GG) Statin 5 78 0.75 (0.25-2.27) 0.6137 Placebo 7 83 1.00 LPAhCV11225994 0.90 0.86 Placebo hom (AA)vs. ref(GG) 0.1018 3 21 1.09(0.37-3.20) 0.8695 0.0412 none het(GA) vs. ref(GG) 24 300 0.65(0.43-0.99) 0.0437 ref (GG) 117 907 1.00 Statin hom (AA)vs. ref(GG)0.2142 5 25 2.34 (1.02-5.35) 0.0449 het(GA) vs. ref (GG) 24 294 1.06(0.68-1.64) 0.8037 ref (GG) 76 989 1.00 Maj Hom(GG) Statin 76 989 0.62(0.47-0.82) 0.0008 Placebo 117 907 1.00 Het(GA) Statin 24 294 1.02(0.59-1.76) 0.9463 Placebo 24 300 1.00 Min Hom(AA) Statin 5 25 1.33(0.35-5.03) 0.6709 Placebo 3 21 1.00 FN1 hCV9506149 0.24 0.28 Placebohom(TT)vs. ref(AA) 0.2100 11 91 0.92 (0.51-1.66) 0.7735 0.0395 none het(TA) vs. ref(AA) 48 500 0.74 (0.53-1.04) 0.0846 ref(AA) 86 645 1.00Statin hom(TT) vs. ref(AA) 0.0985 13 97 1.72 (0.97-3.06) 0.0647 het (TA)vs. ref(AA) 45 525 1.15 (0.78-1.69) 0.4814 ref(AA) 51 691 1.00 MajHom(AA) Statin 51 691 0.58 (0.42-0.81) 0.0015 Placebo 86 645 1.00Het(TA) Statin 45 525 0.90 (0.61-1.33) 0.6010 Placebo 48 500 1.00 MinHom(TT) Statin 13 97 1.10 (0.51-2.33) 0.8125 Placebo 11 91 1.00 PPOXhCV25922816 0.92 0.94 Placebo hom(AA) vs. ref(GG) 0.2414 1 4 1.98(0.34-11.53) 0.4467 0.0463 none het(GA) vs. ref(GG) 21 146 1.25(0.81-1.92) 0.3216) ref(GG) 21 146 1.00 Statin hom(AA) vs. ref(GG) 0 9het(GA) vs. ref(GG) 10 179 0.64 0.34-1.20) 0.1636 ref(GG) 99 1095 1.00Maj Hom(GG) Statin 0.1064 99 1095 0.82 (0.64-1.06) 0.1294 Placebo 21 1461.00 Het(GA) Statin 10 179 0.42 (0.20-0.87) 0.0191 Placebo 21 146 1.00Min Hom(AA) Statin 0 9 Placebo 1 4 1.00 ITGA9 hCV3215409 0.48 0.42Placebo hom(GG) vs. ref(AA) 0.0768 34 225 1.48 (0.96-2.28) 0.0745 0.0435none het (GA)vs. ref(AA) 71 600 1.19 (0.83-1.72) 0.3480 ref(AA) 40 4111.00 Statin hom(GG) vs. ref(AA) 0.2483 10 240 0.54 (0.27-1.06) 0.0744het (GA)vs. ref(AA) 63 629 1.22 (0.82-1.91) 0.3180 ref(AA) 36 447 1.00Maj Hom(AA) Statin 36 447 0.84 (0.55-1.29) 0.4297 Placebo 40 411 1.00Het(GA) Statin 63 629 0.86 (0.62-1.19) 0.3603 Placebo 71 600 1.00 MinHom(GG) Statin 10 240 0.30 (0.15-0.60) 0.0007 Placebo 34 225 1.00 MACF1hCV3112686 0.46 0.42 Placebo hom(GG) vs. ref(CC) 0.1260 29 217 1.38(0.88-2.17) 0.1603 0.0427 HX_ het(GC) vs. ref(CC) 76 592 1.32 0.92-1.90)0.1351 SMOKE ref(CC) 40 424 1.00 Statin hom(GG)vs. ref(CC) 0.1717 12 2280.60 (0.32-1.12) 0.1110 het(GC) vs. ref(CC) 55 620 0.98 (0.67-1.44)0.9179 ref(CC) 42 466 1.00 Maj Hom(CC) Statin 42 466 0.96 (0.63-1.45)0.8310 Placebo 40 424 1.00 Het(GC) Statin 55 620 0.71 (0.51-0.99) 0.0417Placebo 76 592 1.00 Min Hom(GG) Statin 12 228 0.42 (0.22-0.80) 0.0082Placebo 29 217 1.00 IL4R hCV2351160 0.23 0.20 Placebo hom (GG)vs.ref(AA) 0.0514 8 46 1.46 (0.75-2.85) 0.2677 0.0570 HX_ het(GA) vs.ref(AA) 50 393 1.13 (0.82-1.57) 0.4552 SMOKE ref(AA) 86 789 1.00 Statinhom (GG)vs. ref(AA) 0.1343 3 56 0.61 (0.20-1.88) 0.3887 het(GA) vs.ref(AA) 31 447 0.76 (0.51-1.14) 0.1889 ref(AA) 75 811 1.00 Maj Hom(AA)Statin 75 811 0.85 (0.63-1.14) 0.2842 Placebo 86 789 1.00 Het(GA) Statin31 447 0.57 (0.37-0.88) 0.0109 Placebo 50 393 1.00 Min Hom(GG) Statin 356 0.36 (0.10-1.27) 0.1118 Placebo 8 46 1.00 ABCA1 hCV2741051 0.21 0.28Placebo hom(TT) vs. ref(CC) 0.0149 6 84 0.54 (0.24-1.16) 0.1188 0.0369none het(TC) vs. ref(CC) 49 516 0.70 (0.50-0.97) 0.0338 ref(CC) 90 6371.00 Statin hom(TT) vs. ref(CC) 0.5954 9 99 1.14 (0.57-2.19) 0.6981het(TC) vs. ref(CC) 48 555 1.09 (0.75-1.58) 0.6440 ref(CC) 52 662 1.00Maj Hom(CC) Statin 52 662 0.59 (0.42-0.82) 0.0013 Placebo 90 637 1.00Het(TC) Statin 48 555 0.92 (0.62-1.34) 0.6594 Placebo 49 516 1.00 MinHom(TT) Statin 9 99 1.25 (0.45-3.15) 0.6596 Placebo 6 84 1.00 ABCA1hCV2741083 0.93 0.87 Placebo hom (CC)vs. ref(TT) 0.0054 1 18 0.15(0.06-2.51) 0.395 0.0051 none het(TC)vs. ref(TT) 18 275 0.52 (0.32-0.84)0.0063 ref(TT) 126 943 1.00 Statin hom (CC)vs. ref(TT) 0.3109 2 26 1.00(0.25-3.46) 0.9946 het(TC)vs. ref(TT) 30 294 1.29 (0.86-1.91) 0.2178ref(TT) 77 996 1.00 Maj Hom(TT) Statin 77 996 0.61 (0.46-0.80) 0.0003Placebo 126 943 1.00 Het(TC) Statin 30 294 1.51 (0.86-2.57) 0.1517Placebo 18 275 1.00 Min Hom(CC) Statin 2 26 1.36 (0.12-9.07) 0.7966Placebo 1 18 1.00 CYBA hCV2038 0.33 0.34 Placebo hom(AA)vs. ref(GG)0.6072 14 149 0.81 (0.46-1.40) 0.4414 0.0260 hx_smoke het(AG) vs.ref(GG) 68 555 1.05 (0.76-1.44) 0.7862 ref(GG) 63 533 1.00 Statinhom(AA) vs. ref(GG) 0.0086 18 132 2.02 (1.18-3.44) 0.0102 het(AG) vs.ref(GG) 55 612 1.40 (0.94-2.10) 0.1009 ref(GG) 36 571 1.00 Maj Hom(GG)Statin 36 571 0.55 (0.37-0.82) 0.0031 Placebo 63 533 1.00 Het(AG) Statin55 612 0.74 (0.53-1.04) 0.0821 Placebo 68 555 1.00 Min Hom(AA) Statin 18132 1.38 (0.72-2.68) 0.3354 Placebo 14 149 1.00 HLA-DPB1 hCV8851085 0.810.77 Placebo hom(AA) vs. ref(GG) 0.2553 4 66 0.53 (0.19-1.34) 0.68980.0154 hx_smoke het (GA)vs. ref(GG) 48 424 0.93 (0.66-1.29) 0.6823ref(GG) 92 745 1.00 Statin hom(AA) vs. ref(GG) 0.021 8 53 1.97(0.96-3.77) 0.0645 het (GA)vs. ref(GG) 43 445 1.40 (0.95-2.02) 0.085ref(GG) 58 814 1.00 Maj Hom(GG) Statin 58 814 0.58 (0.42-0.80) 0.0009Placebo 92 745 1.00 Het(GA) Statin 43 445 0.87 (0.58-1.29) 0.0501Placebo 48 424 1.00 Min Hom(AA) Statin 8 53 2.19 (0.68-5.87) 0.1805Placebo 4 66 1.00 HSPG2 hCV1603656 0.10 0.08 Placebo hom(TT) vs. ref(CC)0.1704 2 6 2.46 (0.60-6.24) 0.1954 0.0334 hx_smoke het (TC)vs. ref(CC)25 177 1.23 (0.81-1.83) 0.3189 ref(CC) 118 1054 1.00 Statin hom(TT)vs.ref(CC) 0.1033 0 11 N/A 0.9771 het (TC)vs. ref(CC) 11 196 0.65(0.35-1.18) 0.1607 ref(CC) 98 1105 1.00 Maj Hom(CC) Statin 98 1105 0.80(0.62-1.04) 0.0908 Placebo 118 1054 1.00 Het(TC) Statin 11 196 0.42(0.21-0.84) 0.013 Placebo 25 177 1.00 Min Hom(TT) Statin 0 11 N/A 0.9745Placebo 2 6 1.00 HSPG2 hCV1603692 0.08 0.06 Placebo hom(TT)vs. ref(CC)0.1106 1 4 1.98 (0.27-6.86) 0.4769 0.0427 none het (TC)vs. ref(CC) 21130 1.37 (0.88-2.07) 0.1542 ref(CC) 123 1093 1.00 Statin hom(TT) vs.ref(CC) 0.1801 0 6 N/A 0.9829 het (TC)vs. ref(CC) 8 146 0.65 (0.22-1.28)0.2175 ref(CC) 101 1157 1.00 Maj Hom(CC) Statin 101 1157 0.79(0.61-1.02) 0.0712 Placebo 123 1093 1.00 Het(TC) Statin 8 146 0.37(0.17-0.82) 0.0125 Placebo 21 130 1.00 Min Hom(TT) Statin 0 6 N/A 0.9814Placebo 1 4 1.00 HSPG2 hCV1603697 0.08 0.06 Placebo hom(TT) vs. ref(CC)0.0951 1 4 1.99 (0.34-11.59) 0.4431 0.0447 none he t(TC)vs. ref(CC) 21129 1.39 (0.91-2.14) 0.1303 ref(CC) 123 1102 1.00 Statin hom(TT) vs.ref(CC) 0.1749 0 6 N/A 0.9994 het (TC)vs. ref(CC) 8 145 0.65 (0.32-1.32)0.2342 ref(CC) 101 1162 1.00 Maj Hom(CC) Statin 101 1162 0.80(0.62-1.02) 0.0757 Placebo 123 1102 1.00 Het(TC) Statin 8 145 0.37(0.17-0.82) 0.0136 Placebo 21 129 1.00 Min Hom(TT) Statin 0 6 N/A 0.9994Placebo 1 4 1.00 HSPG2 hCV16172339 0.08 0.06 Placebo hom(TT) vs. ref(CC)0.0927 1 4 2.00 (0.27-6.94) 0.4689 0.0927 none het (TC)vs. ref(CC) 21128 1.41 (0.91-2.13) 0.1233 ref(CC) 122 1100 1.00 Statin hom(TT) vs.ref(CC) 0.1728 0 6 N/A 0.983 het (TC)vs. ref(CC) 8 144 0.66 (0.32-1.30)0.2343 ref(CC) 101 1160 1.00 Maj Hom(CC) Statin 101 1160 0.80(0.62-1.03) 0.086 Placebo 122 1100 1.00 Het(TC) Statin 8 144 0.37(0.16-0.82) 0.0124 Placebo 21 128 1.00 Min Hom(TT) Statin 0 6 N/A 0.9815Placebo 1 4 1.00 NPC1 hCV25472673 0.53 0.62 Placebo hom(CC)vs. ref(TT)0.0037 33 173 1.96 (1.28-2.91) 0.0023 0.0093 none het(TC) vs. ref(TT) 70602 1.28 (0.88-1.82) 0.1935 ref(TT) 41 461 1.00 Statin hom(CC)vs.ref(TT) 0.4107 18 215 0.87 (0.51-1.45) 0.6102 het(TC) vs. ref(TT) 43 6010.76 (0.50-1.12) 0.1642 ref(TT) 48 495 1.00 Maj Hom(TT) Statin 48 4951.08 (0.72-1.60) 0.6973 Placebo 41 461 1.00 Het(TC) Statin 43 601 0.61(0.44-0.92) 0.013 Placebo 70 602 1.00 Min Hom(CC) Statin 18 215 0.48(0.27-0.83) 0.008 Placebo 33 173 1.00 NPC1 hCV7490135 0.48 0.53 Placebohom(CC) vs. ref(TT) 0.0754 41 273 1.47 (0.96-2.27) 0.0763 0.0347 nonehet(TC) vs. ref(TT) 70 608 1.17 (0.79-1.72) 0.4402 ref(TT) 34 350 1.00Statin hom(CC) vs. ref(TT) 0.2055 23 283 0.77 (0.47-1.26) 0.3024 het(TC)vs. ref(TT) 46 657 0.67 (0.45-1.01) 0.0552 ref(TT) 40 371 1.00 MajHom(TT) Statin 40 371 1.10 (0.71-1.70) 0.6704 Placebo 34 350 1.00Het(TC) Statin 46 657 0.63 (0.44-0.91) 0.0122 Placebo 70 608 1.00 MinHom(CC) Statin 23 283 0.58 (0.35-0.94) 0.0258 Placebo 41 273 1.00 ^(a)Pvalue for trend ^(b)Number of patients developed recurrent MI during 5years of follow up ^(c)Number of patients had MI ^(d)Relative risk forRMI ^(e)95% confidence interval for relative risk ^(f)Significance ofrisk estimated by Wald test ^(g)P vale for interaction ^(h)Confounders*Y primer nucleotide frequency for cases* *Y primer nucleotide frequencyfor controls**

TABLE 11 Risk of cardiovascular disease events associated withPravastatin, by CD6 genotype, CARE and WOSCOPS N BP Endpoint Gene MarkerStudy CD6 genotype RMI^(a) MI^(b) RR^(e) 95% CI p-value^(g) p value^(h)RMI CD6 hCV2553030 CARE Minor hom (TT) 2 108 0.13 0.03-0.60 0.00160.0342 28 159 Het (TC) 41 489 0.76 0.51-1.12 0.1735 50 442 Major hom(CC) 65 713 0.8 0.59-1.09 0.1518 85 728 recessive (TT) 2 108 0.130.03-0.60 0.0016 0.009 10 64 recessive (TT + CC)ref* 106 1202 0.780.61-1.00 0.0478 135 1170 Csc Cnd ORf 95% CI p-value^(g) BP p value^(h)MI WOSCOPS Minor hom (TT) 7 38 0.23 0.09-0.64 0.0033 0.1126 19 24 Het(TC) 62 198 0.71 0.49-1.04 0.0789 88 200 Major hom (CC) 120 305 0.660.50-0.87 0.0036 179 300 recessive (TT) 7 38 0.23 0.09-0.64 0.00330.0388 19 24 recessive TC + CC)ref* 182 503 0.68 0.54-0.85 0.0007 267500 *Heterozygote and major homozygote was used as reference^(a)Patients developed recurrent MI during 5 years follow up^(b)Patients had MI before entry but didn't developed current MI during5 years follow up ^(c)Patients had MI ^(d)Patients had no MI^(e)relative risk ^(f)Odds ratio ^(g)Wald test ^(h)Breslow's Day p value

TABLE 12 Risk of cardiovascular disease events associated with FCARgenotype in untreated arms, CARE and WOSCOPS Adjusted for Age, Smokingstatus, Gender, hypertension, N Unadjusted Adjusted for Age, Smokingstatus, Gender * BMI, diabetes, baseline LDLD and HDL*, † Endpoint GeneMarker FCARgenotype RMI^(a) MI^(b) OR ∥ 95% CI P ‡ OR ∥ 95% CI Pt OR ∥95% CI P ‡ RMI FCAR hCV7841642 CARE AA 1 11 0.84 (0.11-6.54) 0.87 0.74(0.09-5.89) 0.78 0.86 (0.11-6.71) 0.88 AG 28 159 1.62 (1.04-2.53) 0.0341.58 (1.01-2.48) 0.063 1.58 (1.02-2.46) 0.041 AA + AG 29 170 1.57(1.01-2.43) 0.044 1.52 (0.98-2.37) 0.063 1.58 (1.02-2.46) 0.041 GG ∥ 1161067 1 (ref) 1 (ref) 1 (ref) MI WOSCOPS § Cs^(c) Cn^(d) AA 1 3 0.67(0.07-6.52) 0.73 0.68 (0.07-6.75) 0.75 AG 54 70 1.5 (1.01-2.22) 0.0431.49 (1.00-2.22) 0.05 AA + AG 55 73 1.47 (1.00-2.16) 0.053 1.46(0.98-2.16) 0.061 GG ∥ 233 456 1 (ref) 1 (ref) CARE indicatesCholesterol and Recurrent Events trial; WOSCOPS, West of ScotlandCoronary Prevention Study; RMI; BMI, body-mass index (kg/m2); LDL,low-density lipoprotein; HDL, high-density lipoprotein; OR, odds ratio;CI, confidence interval *Adjusted for age (continuous for CARE, 5-yearage groups for WOSCOPS), smoking (never, former, current) and gender(all male in WOSCOPS) † Further adjusted for history of hypertension,BMI (continuous), history of diabetes, baseline LDL level (continuous),and baseline HDL level (continuous) ‡ Wald test § Conditional logisticregression used to account for matching of WOSCOPS cases and controls(all male) on smoking and age ∥ Major homozygote (AspAsp) was used asreference ^(a)Patients developed recurrent MI during 5 years follow up^(b)Patients had MI before entry but didn't developed current MI during6 years follow up ^(c)Patients had MI ^(d)Patients had no MI Risk ofcardiovascular disease events associated with Pravastatin, by FCARgenotype, CARE and WOSCOPS Adjusted for Age, Smoking status, Gender,hypertension, Adjusted for Age, Smoking BMI, diabetes, baseline LDLDFCAR Unadjusted status, Gender* and HDL*, † Endpoint Gene Marker Studygenotype **OR 95% CI P‡ **OR 95% CI P ‡ **OR 95% CI P ‡ RMI FCARhCV7841642 CARE AA + AG 0.32 (0.15-0.67) 0.0016 0.31 (0.15-0.65) 0.00210.31 (0.15-0.67) 0.0026 GG 0.81 (0.61-1.07) 0.13 0.79 (0.60-1.06) 0.120.79 (0.60-1.05) 0.11 p interaction: 0.0163 § p interaction: 0.0151 § pinteraction: 0.0193 § MI WOSCOPS ∥ AA + AG 0.57 (0.34-0.95) 0.031 0.55(0.32-0.93) 0.025 GG 0.66 (0.52-0.84) 0.0008 0.65 (0.51-0.83) 0.0006 pinteraction: 0.5851 § p interaction: 0.5480 § CARE indicates Cholesteroland Recurrent Events trial; WOSCOPS, West of Scotland CoronaryPrevention Study; RMI, recurrent myocardial infarction; LDL, low-densitylipoprotein; HDL, high-density lipoprotein; OR, odds ratio; CI,confidence interval; BMI, body-mass index (kg/m2) *Adjusted for age(continuous in CARE, 5-year age groups in WOSCOPS), smoking (never,former, current) and gender (all male in WOSCOPS) † Further adjusted forhistory of hypertension, BMI (continuous), history of diabetes, baselineLDL level (continuous), and baseline HDL level (continuous) ‡ Wald test§ Likelihood ratio test of interaction between treatment and FCARgenotype ∥ Conditional logistic regression used to account for matchingof WOSCOPS cases and controls on smoking and age **Placebo group wasused as reference

TABLE 13 Statistically Significant Interactions Between SNP InteractionGenotypes and Pravastatin Efficacy for Two Overall* Effect** CVD CaseDefinitions: Fatal MI/Sudden Death/Definite Control Chi-SquareChi-Square Non-fatal MI and Fatal/Non-fatal MI Group Test Test CaseDefin- Stra- Sta- p- Sta- p- Public Marker Study Study Design Definitionition*** tum tistic value tistic value ABCA1 hCV2741083 CARE ProspectiveF MI/SD/NF MI Cleaner WM 15.1 0.0099 7.68 0.0215 ABCA1 hCV2741083 CARECase/Control F MI/SD/NF MI Cleaner WM 12.96 0.0237 6.56 0.0377 ADAMTS1hCV529706 CARE Case/Control F MI/SD/NF MI Cleaner WM 12.79 0.0254 6.440.0399 ADAMTS1 hCV529710 CARE Case/Control F MI/SD/NF MI Cleaner WM13.42 0.0197 6.54 0.038 AGTR1 hCV3187716 CARE Prospective F MI/SD/NF MIAll Possible WM 12.22 0.032 8.25 0.0162 AGTR1 hCV3187716 CAREProspective F MI/SD/NF MI Cleaner WM 14.41 0.0132 7.65 0.0218 AGTR1hCV3187716 CARE Case/Control F MI/SD/NF MI Cleaner WM 11.97 0.0352 6.930.0313 ASAH1 hCV2442143 CARE Prospective F MI/SD/NF MI Cleaner WM 15.620.008 6.23 0.0445 CAPG hCV15851292 CARE Case/Control F MI/SD/NF MICleaner WM 12.24 0.0317 7.57 0.0227 CAPN10 hCV25614016 CARE ProspectiveF MI/SD/NF MI All Possible WM 11.48 0.0427 8.83 0.0121 CAPN10hCV25614016 CARE Prospective F MI/SD/NF MI Cleaner WM 14.29 0.0138 8.280.016 CAPN10 hCV25614016 CARE Case/Control F MI/SD/NF MI All Possible WM11.5 0.0424 9.06 0.0108 CAPN10 hCV25614016 CARE Case/Control F MI/SD/NFMI Cleaner WM 13.12 0.0222 8.11 0.0173 CAPN2 hCV781558 W Case/Control FMI/SD/NF MI All Possible WM 27.51 <.0001 10.68 0.0048 CAPN2 hCV781558 WCase/Control F MI/SD/NF MI Cleaner WM 29.73 <.0001 10.14 0.0063 CCL11hCV7449808 W Case/Control F MI/SD/NF MI All Possible WM 22.55 0.00049.09 0.0106 CCL11 hCV7449808 W Case/Control F MI/SD/NF MI Cleaner WM25.38 0.0001 10.38 0.0056 CD163 hCV25591528 CARE Prospective F MI/SD/NFMI All Possible WM 12.05 0.0341 9.01 0.0111 CD163 hCV25591528 CAREProspective F MI/SD/NF MI Cleaner WM 14.48 0.0129 7.65 0.0218 CD163hCV25591528 CARE Case/Control F MI/SD/NF MI All Possible WM 12.87 0.024710.44 0.0054 CD163 hCV25591528 CARE Case/Control F MI/SD/NF MI CleanerWM 15.08 0.01 9.01 0.011 CD6 hCV2553030 CARE Prospective F MI/SD/NF MIAll Possible WM 11.51 0.0422 6.86 0.0323 CD6 hCV2553030 CARE ProspectiveF MI/SD/NF MI Cleaner WM 15.89 0.0072 7.8 0.0202 CD6 hCV2553030 CARECase/Control F MI/SD/NF MI All Possible WM 12.22 0.0318 12.46 0.002 CD6hCV2553030 CARE Case/Control F MI/SD/NF MI Cleaner WM 16.02 0.0068 13.780.001 CD6 hCV25922320 CARE Prospective F MI/SD/NF MI All Possible WM12.15 0.0327 9.27 0.0097 CD6 hCV25922320 CARE Prospective F MI/SD/NF MICleaner WM 16.27 0.0061 9.94 0.0069 CD6 hCV25922320 CARE Case/Control FMI/SD/NF MI All Possible WM 12.46 0.029 9..4 0.0094 CD6 hCV25922320 CARECase/Control F MI/SD/NF MI Cleaner WM 17.95 0.003 12.05 0.0024 COL6A2hCV2811372 W Case/Control F MI/SD/NF MI All Possible WM 21.94 0.00058.17 0.0168 COL6A2 hCV2811372 W Case/Control F MI/SD/NF MI Cleaner WM22.35 0.0004 7.28 0.0262 CR1 hCV25598594 CARE Prospective F MI/SD/NF MIAll Possible WM 8.5 0.0367 4.68 0.0305 CR1 hCV25598594 CARE ProspectiveF MI/SD/NF MI Cleaner WM 12.88 0.0049 5.2 0.0225 CR1 hCV25598594 CARECase/Control F MI/SD/NF MI All Possible WM 8.11 0.0437 7.14 0.0076 CR1hCV25598594 CARE Case/Control F MI/SD/NF MI Cleaner WM 11.87 0.0079 7.820.0052 CXCL16 hCV8718197 CARE Prospective F MI/SD/NF MI Cleaner WM 15.80.0075 8.88 0.0118 CXCL16 hCV8718197 CARE Case/Control F MI/SD/NF MICleaner WM 15.74 0.0076 9.25 0.0098 ELN hCV1253630 CARE Prospective FMI/SD/NF MI Cleaner WM 12.02 0.0345 6.79 0.0336 ELN hCV1253630 CARECase/Control F MI/SD/NF MI Cleaner WM 11.34 0.045 6.77 0.0338 FCARhCV7841642 CARE Prospective F MI/SD/NF MI Cleaner WM 13.17 0.0218 6.220.0445 FGB hCV7429784 W Case/Control F MI/SD/NF MI All Possible WM 24.080.0002 6.19 0.0453 GALC hCV25922440 CARE Prospective F MI/SD/NF MICleaner WM 11.27 0.0463 7.21 0.0273 GAPD hCV8921288 W Case/Control FMI/SD/NF MI All Possible WM 23.92 0.0002 6.94 0.0312 GAPD hCV8921288 WCase/Control F MI/SD/NF MI Cleaner WM 27.62 <.0001 9.78 0.0075 HLA-DPB1hCV25651174 CARE Prospective F MI/SD/NF MI All Possible WM 15.04 0.010210.82 0.0045 HLA-DPB1 hCV25651174 CARE Prospective F MI/SD/NF MI CleanerWM 20.44 0.001 12.43 0.002 HLA-DPB1 hCV25651174 CARE Case/Control FMI/SD/NF MI All Possible WM 15.47 0.0085 13.5 0.0012 HLA-DPB1hCV25651174 CARE Case/Control F MI/SD/NF MI Cleaner WM 20.65 0.000916.15 0.0003 HLA-DPB1 hCV8851065 CARE Prospective F MI/SD/NF MI AllPossible WM 13.92 0.0161 9.18 0.0102 HLA-DPB1 hCV8851065 CAREProspective F MI/SD/NF MI Cleaner WM 18.72 0.0022 10.22 0.006 HLA-DPB1hCV8851065 CARE Case/Control F MI/SD/NF MI All Possible WM 14.95 0.010612.1 0.0024 HLA-DPB1 hCV8851065 CARE Case/Control F MI/SD/NF MI CleanerWM 19.13 0.0018 14.06 0.0009 HLA-DPB1 hCV8851084 CARE Prospective FMI/SD/NF MI Cleaner WM 12.61 0.0274 6.21 0.0448 HLA-DPB1 hCV8851084 CARECase/Control F MI/SD/NF MI Cleaner WM 13.34 0.0204 8.54 0.0139 HLA-DPB1hCV8851084 CARE Prospective F MI/SD/NF MI Cleaner WM 13.85 0.0166 7.870.0196 HLA-DPB1 hCV8851084 CARE Case/Control F MI/SD/NF MI Cleaner WM14.28 0.0139 9.61 0.0082 HLA-DQB1 hCV9494470 CARE Prospective F MI/SD/NFMI All Possible WM 11.15 0.0484 8.63 0.0134 HLA-DQB1 hCV9494470 CAREProspective F MI/SD/NF MI Cleaner WM 14.11 0.0149 8.51 0.0142 HLA-DQB1hCV9494470 CARE Case/Control F MI/SD/NF MI All Possible WM 11.7 0.03919.42 0.009 HLA-DQB1 hCV9494470 CARE Case/Control F MI/SD/NF MI CleanerWM 14.73 0.0116 9.71 0.0078 HRC hCV11506744 W Case/Control F MI/SD/NF MIAll Possible WM 23.8 0.0002 10.36 0.0056 HRC hCV11506744 W Case/ControlF MI/SD/NF MI Cleaner WM 25.89 <.0001 10.62 0.0049 IL1A hCV9546471 WCase/Control F MI/SD/NF MI All Possible WM 22.89 0.0004 7.64 0.022 IL1AhCV9546471 W Case/Control F MI/SD/NF MI Cleaner WM 24.29 0.0002 6.790.0335 IL1RN hCV8737990 CARE Prospective F MI/SD/NF MI Cleaner WM 14.440.0131 7.62 0.0222 IL1RN hCV8737990 CARE Case/Control F MI/SD/NF MICleaner WM 13 0.0234 6.52 0.0384 IL4R hCV2769554 CARE Case/Control FMI/SD/NF MI All Possible WM 14.49 0.0128 6.76 0.0341 IL4R hCV2769554CARE Case/Control F MI/SD/NF MI Cleaner WM 14.58 0.0123 6.12 0.0469ITGAE hCV1243283 CARE Case/Control F MI/SD/NF MI Cleaner WM 13.01 0.02336.66 0.0357 KDR hCV16192174 CARE Prospective F MI/SD/NF MI Cleaner WM14.39 0.0133 6.44 0.04 KDR hCV16192174 CARE Case/Control F MI/SD/NF MIAll Possible WM 13.72 0.0175 8.04 0.0179 KDR hCV16192174 CARECase/Control F MI/SD/NF MI Cleaner WM 16.55 0.0054 9.34 0.0094 KDRhCV22271999 CARE Prospective F MI/SD/NF MI Cleaner WM 14.38 0.0133 6.450.0397 KDR hCV22271999 CARE Case/Control F MI/SD/NF MI All Possible WM13.78 0.0171 8.11 0.0174 KDR hCV22271999 CARE Case/Control F MI/SD/NF MICleaner WM 16.66 0.0052 9.48 0.0087 KLK14 hCV16044337 CARE Prospective FMI/SD/NF MI All Possible WM 17.43 0.0037 8.78 0.0124 KLK14 hCV16044337CARE Prospective F MI/SD/NF MI Cleaner WM 18.02 0.0029 7.27 0.0264 KLK14hCV16044337 CARE Case/Control F MI/SD/NF MI All Possible WM 17.18 0.00429.22 0.01 KLK14 hCV16044337 CARE Case/Control F MI/SD/NF MI Cleaner WM18.67 0.0022 7.63 0.022 LRP3 hCV25594815 W Case/Control F MI/SD/NF MIAll Possible WM 24 0.0002 11.17 0.0038 LRP3 hCV25594815 W Case/Control FMI/SD/NF MI Cleaner WM 26.51 <.0001 11.9 0.0026 MICA hCV25474101 CARECase/Control F MI/SD/NF MI Cleaner WM 14.22 0.0143 6.69 0.0353 MYH7hCV25629396 CARE Prospective F MI/SD/NF MI All Possible WM 13.09 0.00446.8 0.0091 MYH7 hCV25629396 CARE Prospective F MI/SD/NF MI Cleaner WM 170.0007 7.26 0.007 MYH7 hCV25629396 CARE Case/Control F MI/SD/NF MI AllPossible WM 12.96 0.0047 9.81 0.0017 MYH7 hCV25629396 CARE Case/ControlF MI/SD/NF MI Cleaner WM 14.74 0.0021 9.47 0.0021 NOS3 hCV3219460 CAREProspective F MI/SD/NF MI All Possible WM 11.76 0.0382 6.75 0.0342 NOS3hCV3219460 CARE Prospective F MI/SD/NF MI Cleaner WM 14.69 0.0118 7.470.0239 NOS3 hCV3219460 CARE Case/Control F MI/SD/NF MI All Possible WM12.02 0.0346 7.45 0.0242 NOS3 hCV3219460 CARE Case/Control F MI/SD/NF MICleaner WM 14.78 0.0114 7.98 0.0185 NPC1 hCV25472673 CARE Prospective FMI/SD/NF MI All Possible WM 11.68 0.0394 6.39 0.0409 NPC1 hCV25472673CARE Prospective F MI/SD/NF MI Cleaner WM 21.8 0.0006 11.02 0.004 NPC1hCV25472673 CARE Case/Control F MI/SD/NF MI Cleaner WM 19.06 0.0019 9.810.0074 PLAB hCV7494810 CARE Prospective F MI/SD/NF MI All Possible WM11.47 0.0429 6.87 0.0322 PLAB hCV7494810 CARE Prospective F MI/SD/NF MICleaner WM 14.7 0.0117 6.06 0.0483 PLAB hCV7494810 CARE Case/Control FMI/SD/NF MI All Possible WM 11.35 0.0449 7.37 0.0251 PLAB hCV7494810CARE Case/Control F MI/SD/NF MI Cleaner WM 14.84 0.0111 7.43 0.0244PRKCQ hCV15954277 CARE Prospective F MI/SD/NF MI All Possible WM 13.470.0194 9.75 0.0077 PRKCQ hCV15954277 CARE Prospective F MI/SD/NF MICleaner WM 11.96 0.0354 6.08 0.0479 PRKCQ hCV15954277 CARE Case/ControlF MI/SD/NF MI All Possible WM 12.34 0.0304 9.38 0.0092 SERPINA5hCV9596963 CARE Case/Control F MI/SD/NF MI All Possible WM 12.27 0.03136.41 0.0405 SN hCV25623265 CARE Prospective F MI/SD/NF MI Cleaner WM14.96 0.0105 8.54 0.014 SN hCV25623265 CARE Case/Control F MI/SD/NF MICleaner WM 15.1 0.01 9.75 0.0076 TAP1 hCV549926 CARE Prospective FMI/SD/NF MI All Possible WM 13.9 0.0163 7.13 0.0283 TAP1 hCV549926 CAREProspective F MI/SD/NF MI Cleaner WM 14.3 0.0138 6.22 0.0447 TAP1hCV549926 CARE Case/Control F MI/SD/NF MI All Possible WM 13.04 0.0239.44 0.0089 TAP1 hCV549926 CARE Case/Control F MI/SD/NF MI Cleaner WM12.88 0.0245 8.15 0.017 TIMP2 hCV25629888 CARE Case/Control F MI/SD/NFMI Cleaner WM 14.43 0.0131 6.69 0.0352 TNF hCV7514879 CARE Prospective FMI/SD/NF MI Cleaner WM 14.06 0.0153 7.17 0.0278 TNF hCV7514879 CARECase/Control F MI/SD/NF MI Cleaner WM 12.72 0.0261 6.07 0.0481 VTNhCV2536595 CARE Prospective F MI/SD/NF MI All Possible WM 12.97 0.02377.6 0.0224 VTN hCV2536595 CARE Prospective F MI/SD/NF MI Cleaner WM14.43 0.0131 6.14 0.0463 VTN hCV2536595 CARE Case/Control F MI/SD/NF MIAll Possible WM 13 0.0234 7.42 0.0244 VTN hCV2536595 CARE Case/Control FMI/SD/NF MI Cleaner WM 14.88 0.0109 6.93 0.0313 A2M hCV517658 CARECase/Control F&NF MI All Possible WM 15.24 0.0094 6.84 0.0327 A2MhCV517658 CARE Case/Control F&NF MI Cleaner WM 17.54 0.0036 6.16 0.046ABCA1 hCV2741051 CARE Prospective F&NF MI All Possible WM 13.87 0.01657.96 0.0187 ABCA1 hCV2741051 CARE Prospective F&NF MI Cleaner WM 16.340.0059 6.38 0.0411 ABCA1 hCV2741051 CARE Case/Control F&NF MI AllPossible WM 13.37 0.0202 7.64 0.0219 ABCA1 hCV2741051 CARE Case/ControlF&NF MI Cleaner WM 15.31 0.0091 6.25 0.044 ABCA1 hCV2741083 CAREProspective F&NF MI All Possible WM 16.94 0.0046 7.99 0.0184 ABCA1hCV2741083 CARE Prospective F&NF MI Cleaner WM 21.26 0.0007 8 0.0183ABCA1 hCV2741083 CARE Case/Control F&NF MI All Possible WM 16.64 0.00527.83 0.02 ABCA1 hCV2741083 CARE Case/Control F&NF MI Cleaner WM 18.670.0022 6.53 0.0382 ADAM12 hCV25928135 CARE Case/Control F&NF MI AllPossible WM 17.71 0.0033 6.92 0.0315 ADAM12 hCV25928135 CARECase/Control F&NF MI Cleaner WM 19.51 0.0015 7.5 0.0235 ALOX12hCV1552894 CARE Prospective F&NF MI All Possible WM 13.01 0.0233 6.50.0389 ALOX12 hCV1552900 CARE Prospective F&NF MI All Possible WM 13.220.0214 6.49 0.039 C14orf159 hCV25472345 CARE Prospective F&NF MI AllPossible WM 11.44 0.0433 6.05 0.0486 C14orf159 hCV25472345 CARECase/Control F&NF MI All Possible WM 11.83 0.0372 6.4 0.0408 CAPN2hCV781558 W Case/Control F&NF MI All Possible WM 23.75 0.0002 8.920.0115 CAPN2 hCV781558 W Case/Control F&NF MI Cleaner WM 26.05 <.00018.88 0.0118 CCL11 hCV7449808 W Case/Control F&NF MI All Possible WM21.25 0.0007 10.28 0.0059 CCL11 hCV7449808 W Case/Control F&NF MICleaner WM 23.44 0.0003 10.88 0.0043 CD163 hCV25591528 CARE ProspectiveF&NF MI All Possible WM 15.1 0.01 9.22 0.01 CD163 hCV25591528 CAREProspective F&NF MI Cleaner WM 18.28 0.0026 7.82 0.0201 CD163hCV25591528 CARE Case/Control F&NF MI All Possible WM 15.62 0.008 10.50.0052 CD163 hCV25591528 CARE Case/Control F&NF MI Cleaner WM 18.720.0022 9.13 0.0104 CD6 hCV2553030 CARE Prospective F&NF MI All PossibleWM 12.37 0.0301 6.35 0.0418 CD6 hCV2553030 CARE Prospective F&NF MICleaner WM 17.24 0.0041 7.6 0.0224 CD6 hCV2553030 CARE Case/Control F&NFMI All Possible WM 12.41 0.0295 8.44 0.0147 CD6 hCV2553030 CARECase/Control F&NF MI Cleaner WM 17.04 0.0044 10.19 0.0061 COL11A1hCV8400671 CARE Case/Control F&NF MI All Possible WM 11.4 0.044 7.450.0241 COL2A1 hCV3276196 CARE Case/Control F&NF MI Cleaner WM 17.860.0031 6.29 0.0431 CR1 hCV25598594 CARE Prospective F&NF MI All PossibleWM 11.12 0.0111 4.98 0.0256 CR1 hCV25598594 CARE Prospective F&NF MICleaner WM 16.21 0.001 5.53 0.0187 CR1 hCV25598594 CARE Case/ControlF&NF MI All Possible WM 11.01 0.0117 6.69 0.0097 CR1 hCV25598594 CARECase/Control F&NF MI Cleaner WM 15.25 0.0016 6.94 0.0084 CXCL16hCV8718197 CARE Prospective F&NF MI All Possible WM 14.38 0.0134 9.020.011 CXCL16 hCV8718197 CARE Prospective F&NF MI Cleaner WM 19.81 0.001410.87 0.0044 CXCL16 hCV8718197 CARE Case/Control F&NF MI All Possible WM14.48 0.0128 9.07 0.0107 CXCL16 hCV8718197 CARE Case/Control F&NF MICleaner WM 19.69 0.0014 11.26 0.0036 CYBA hCV2038 CARE Case/Control F&NFMI All Possible WM 12.79 0.0254 6.61 0.0367 DDEF1 hCV7686234 WCase/Control F&NF MI All Possible WM 18.21 0.0027 6.17 0.0458 ELNhCV1253630 CARE Prospective F&NF MI All Possible WM 15.02 0.0103 9.30.0095 ELN hCV1253630 CARE Prospective F&NF MI Cleaner WM 19.02 0.001910.25 0.006 ELN hCV1253630 CARE Case/Control F&NF MI All Possible WM16.86 0.0048 11.05 0.004 ELN hCV1253630 CARE Case/Control F&NF MICleaner WM 19.18 0.0018 11.09 0.0039 F13A1 hCV11972326 CARE Case/ControlF&NF MI All Possible WM 12.42 0.0294 6.28 0.0433 F7 hCV783138 CAREProspective F&NF MI All Possible WM 13.6 0.0183 8.4 0.015 F7 hCV783138CARE Prospective F&NF MI Cleaner WM 15.55 0.0082 7.11 0.0287 F7hCV783138 CARE Case/Control F&NF MI All Possible WM 12.8 0.0254 7.750.0208 F7 hCV783138 CARE Case/Control F&NF MI Cleaner WM 14.16 0.01466.31 0.0425 F7 hCV783184 CARE Prospective F&NF MI All Possible WM 11.840.037 6.64 0.0362 F7 hCV783184 CARE Case/Control F&NF MI All Possible WM11.65 0.0398 6.42 0.0403 FABP1 hCV16173091 CARE Prospective F&NF MI AllPossible WM 11.41 0.0439 6.21 0.0449 FABP1 hCV16173091 CARE ProspectiveF&NF MI Cleaner WM 15.31 0.0091 6.42 0.0404 FABP1 hCV16173091 CARECase/Control F&NF MI Cleaner WM 14.49 0.0128 6.02 0.0492 FCAR hCV7841642CARE Case/Control F&NF MI All Possible WM 11.78 0.038 6.15 0.0461 FN1hCV9506149 CARE Case/Control F&NF MI All Possible WM 13.4 0.0199 6.050.0485 GALC hCV25922440 CARE Prospective F&NF MI Cleaner WM 13.79 0.0176.1 0.0473 GAPD hCV8921288 CARE Prospective F&NF MI Cleaner WM 15.40.0088 6.93 0.0313 GAPD hCV8921288 CARE Case/Control F&NF MI AllPossible WM 11.36 0.0447 6.14 0.0465 GAPD hCV8921288 W Case/Control F&NFMI All Possible WM 19.53 0.0015 7.65 0.0219 GAPD hCV8921288 CARECase/Control F&NF MI Cleaner WM 14.21 0.0144 6.66 0.0358 GAPD hCV8921288W Case/Control F&NF MI Cleaner WM 23.91 0.0002 10.29 0.0058 HLA-DPB1hCV25651174 CARE Prospective F&NF MI All Possible WM 13.57 0.0186 7.760.0207 HLA-DPB1 hCV25651174 CARE Prospective F&NF MI Cleaner WM 20.310.0011 9.88 0.0072 HLA-DPB1 hCV25651174 CARE Case/Control F&NF MI AllPossible WM 13.9 0.0163 9 0.0111 HLA-DPB1 hCV25651174 CARE Case/ControlF&NF MI Cleaner WM 20.01 0.0012 11.53 0.0031 HLA-DPB1 hCV8851065 CAREProspective F&NF MI All Possible WM 14.29 0.0139 8.35 0.0154 HLA-DPB1hCV8851065 CARE Prospective F&NF MI Cleaner WM 19.31 0.0017 9.3 0.0095HLA-DPB1 hCV8851065 CARE Case/Control F&NF MI All Possible WM 14.940.0106 10.01 0.0067 HLA-DPB1 hCV8851065 CARE Case/Control F&NF MICleaner WM 19.39 0.0016 11.48 0.0032 HLA-DPB1 hCV8851084 CAREProspective F&NF MI Cleaner WM 17.32 0.0039 6.89 0.032 HLA-DPB1hCV8851084 CARE Case/Control F&NF MI All Possible WM 12.93 0.0241 7.810.0202 HLA-DPB1 hCV8851084 CARE Case/Control F&NF MI Cleaner WM 17.990.003 9.78 0.0075 HLA-DPB1 hCV8851085 CARE Prospective F&NF MI AllPossible WM 11.72 0.0388 6.08 0.048 HLA-DPB1 hCV8851085 CARE ProspectiveF&NF MI Cleaner WM 17.88 0.0031 8.02 0.0182 HLA-DPB1 hCV8851085 CARECase/Control F&NF MI All Possible WM 12.2 0.0322 7.44 0.0242 HLA-DPB1hCV8851085 CARE Case/Control F&NF MI Cleaner WM 18.1 0.0028 10.1 0.0064HLA-DQB1 hCV9494470 CARE Prospective F&NF MI All Possible WM 12.370.0301 6.1 0.0474 HLA-DQB1 hCV9494470 CARE Prospective F&NF MI CleanerWM 16.24 0.0062 6.35 0.0417 HLA-DQB1 hCV9494470 CARE Case/Control F&NFMI All Possible WM 12.01 0.0347 6.05 0.0485 HLA-DQB1 hCV9494470 CARECase/Control F&NF MI Cleaner WM 16.35 0.0059 6.75 0.0347 HRC hCV11506744W Case/Control F&NF MI All Possible WM 18.27 0.0026 7.55 0.023 HRChCV11506744 W Case/Control F&NF MI Cleaner WM 20.75 0.0009 8.06 0.0177IL1A hCV9546471 W Case/Control F&NF MI All Possible WM 20.88 0.0009 6.20.0451 IL1RN hCV8737990 CARE Prospective F&NF MI All Possible WM 13.280.0209 6.11 0.047 IL1RN hCV8737990 CARE Prospective F&NF MI Cleaner WM19.22 0.0017 8.15 0.017 IL1RN hCV8737990 CARE Case/Control F&NF MICleaner WM 17.24 0.0041 7.18 0.0276 IL9 hCV3275199 CARE Prospective F&NFMI All Possible WM 18.13 0.0028 12.38 0.0021 IL9 hCV3275199 CAREProspective F&NF MI Cleaner WM 19.78 0.0014 10.69 0.0048 IL9 hCV3275199CARE Case/Control F&NF MI All Possible WM 17.77 0.0032 13.04 0.0015 IL9hCV3275199 CARE Case/Control F&NF MI Cleaner WM 18.5 0.0024 10.68 0.0048ITGA4 hCV7618856 CARE Prospective F&NF MI All Possible WM 10.26 0.0165 40.0455 ITGA4 hCV7618856 CARE Case/Control F&NF MI All Possible WM 11.670.0086 5.77 0.0163 ITGA4 hCV7618856 CARE Case/Control F&NF MI Cleaner WM13.44 0.0038 4.75 0.0292 KDR hCV16192174 CARE Prospective F&NF MI AllPossible WM 16.78 0.0049 8.22 0.0164 KDR hCV16192174 CARE ProspectiveF&NF MI Cleaner WM 19.35 0.0017 8.21 0.0165 KDR hCV16192174 CARECase/Control F&NF MI All Possible WM 19.22 0.0017 10.15 0.0062 KDRhCV16192174 CARE Case/Control F&NF MI Cleaner WM 21.49 0.0007 10.880.0044 KDR hCV22271999 CARE Prospective F&NF MI All Possible WM 16.690.0051 8.1 0.0174 KDR hCV22271999 CARE Prospective F&NF MI Cleaner WM19.38 0.0016 8.15 0.017 KDR hCV22271999 CARE Case/Control F&NF MI AllPossible WM 19.26 0.0017 10.16 0.0062 KDR hCV22271999 CARE Case/ControlF&NF MI Cleaner WM 21.61 0.0006 10.95 0.0042 KLK14 hCV16044337 CAREProspective F&NF MI All Possible WM 20.37 0.0011 7.7 0.0212 KLK14hCV16044337 CARE Prospective F&NF MI Cleaner WM 21.38 0.0007 6.24 0.0442KLK14 hCV16044337 CARE Case/Control F&NF MI All Possible WM 20.43 0.0017.96 0.0186 KLK14 hCV16044337 CARE Case/Control F&NF MI Cleaner WM 22.240.0005 6.75 0.0343 LPA hCV11225994 CARE Case/Control F&NF MI Cleaner WM23.9 0.0002 6.86 0.0325 LRP3 hCV25594815 W Case/Control F&NF MI AllPossible WM 19.66 0.0014 9.94 0.0069 LRP3 hCV25594815 W Case/ControlF&NF MI Cleaner WM 21.99 0.0005 10.2 0.0061 MYH7 hCV25629396 CAREProspective F&NF MI All Possible WM 19.04 0.0003 9.53 0.002 MYH7hCV25629396 CARE Prospective F&NF MI Cleaner WM 22.27 <.0001 9.49 0.0021MYH7 hCV25629396 CARE Case/Control F&NF MI All Possible WM 19.29 0.000211.83 0.0006 MYH7 hCV25629396 CARE Case/Control F&NF MI Cleaner WM 20.590.0001 10.99 0.0009 NOS3 hCV3219460 CARE Prospective F&NF MI AllPossible WM 11.33 0.0452 6.1 0.0474 NOS3 hCV3219460 CARE ProspectiveF&NF MI Cleaner WM 15.17 0.0097 6.72 0.0347 NOS3 hCV3219460 CARECase/Control F&NF MI All Possible WM 11.36 0.0447 6.52 0.0384 NOS3hCV3219460 CARE Case/Control F&NF MI Cleaner WM 14.56 0.0124 6.79 0.0335NPC1 hCV25472673 CARE Prospective F&NF MI Cleaner WM 24.23 0.0002 10.080.0065 NPC1 hCV25472673 CARE Case/Control F&NF MI Cleaner WM 21.330.0007 8.55 0.0139 NPC1 hCV7490135 CARE Prospective F&NF MI Cleaner WM15.4 0.0088 6.22 0.0446 PLAB hCV7494810 CARE Prospective F&NF MI AllPossible WM 12.41 0.0296 6.11 0.047 PLAB hCV7494810 CARE Case/ControlF&NF MI All Possible WM 12.67 0.0267 6.61 0.0368 PLAB hCV7494810 CARECase/Control F&NF MI Cleaner WM 16.31 0.006 6.33 0.0421 PPOX hCV25922816CARE Prospective F&NF MI All Possible WM 11.43 0.0435 6.78 0.0338 PPOXhCV25922816 CARE Prospective F&NF MI Cleaner WM 18.35 0.0025 8.32 0.0156PPOX hCV25922816 CARE Case/Control F&NF MI All Possible WM 11.4 0.0447.47 0.0239 PPOX hCV25922816 CARE Case/Control F&NF MI Cleaner WM 15.050.0102 7.25 0.0267 SELL hCV16172571 CARE Prospective F&NF MI AllPossible WM 15.39 0.0088 7.03 0.0297 SELL hCV16172571 CARE Case/ControlF&NF MI All Possible WM 15.17 0.0097 7.24 0.0268 SELL hCV25474627 CAREProspective F&NF MI All Possible WM 14.9 0.0108 7.4 0.0249 SELLhCV25474627 CARE Case/Control F&NF MI All Possible WM 14.83 0.0111 7.680.0215 SERPINA1 hCV25640504 CARE Prospective F&NF MI Cleaner WM 14.880.0109 6.03 0.0491 SERPINA1 hCV25640504 CARE Case/Control F&NF MICleaner WM 14.68 0.0118 7.06 0.0293 SERPINA5 hCV9596963 CARE ProspectiveF&NF MI All Possible WM 15.87 0.0072 9.13 0.0104 SERPINA5 hCV9596963CARE Prospective F&NF MI Cleaner WM 20.59 0.001 8.37 0.0152 SERPINA5hCV9596963 CARE Case/Control F&NF MI All Possible WM 16.98 0.0045 9.240.0099 SERPINA5 hCV9596963 CARE Case/Control F&NF MI Cleaner WM 19.950.0013 7.74 0.0209 SERPINB6 hCV16190893 CARE Prospective F&NF MI AllPossible WM 14.61 0.0122 8.86 0.0119 SERPINB6 hCV16190893 CAREProspective F&NF MI Cleaner WM 16.56 0.0054 7.42 0.0245 SERPINB6hCV16190893 CARE Case/Control F&NF MI All Possible WM 14.41 0.0132 9.190.0101 SERPINB6 hCV16190893 CARE Case/Control F&NF MI Cleaner WM 16.730.005 8.64 0.0133 SERPINI2 hCV370782 CARE Prospective F&NF MI AllPossible WM 17.89 0.0031 9.64 0.0081 SERPINI2 hCV370782 CARE ProspectiveF&NF MI Cleaner WM 21.19 0.0007 8.65 0.0132 SERPINI2 hCV370782 CARECase/Control F&NF MI All Possible WM 16.78 0.0049 8.88 0.0118 SERPINI2hCV370782 CARE Case/Control F&NF MI Cleaner WM 18.6 0.0023 7.91 0.0191TNF hCV7514879 CARE Prospective F&NF MI Cleaner WM 19.06 0.0019 8.550.0139 TNF hCV7514879 CARE Case/Control F&NF MI Cleaner WM 17.78 0.00327.77 0.0206 VTN hCV2536595 CARE Prospective F&NF MI All Possible WM18.29 0.0026 7.52 0.0232 VTN hCV2536595 CARE Prospective F&NF MI CleanerWM 19.68 0.0014 6.07 0.0481 VTN hCV2536595 CARE Case/Control F&NF MI AllPossible WM 18.11 0.0028 7.48 0.0237 VTN hCV2536595 CARE Case/ControlF&NF MI Cleaner WM 20.02 0.0012 6.98 0.0305 Statistically SignificantInteractions Between SNP Genotypes and Pravastatin Efficacy for Two CVDCase Definitions: Fatal MI/Sudden Death/Definite Pravastatin vs. PlaceboOdds Ratio (95% CI) Non-fatal MI and 0 Rare Alleles n/total (%) 1 RareAllele n/total (%) 2 Rare Alleles n/total (%) Patients Patients Patientswith Signifi- Fatal/Non-fatal MI Pravastatin Placebo Pravastatin PlaceboPravastatin Placebo with 0 Rare with 1 2 Rare cance Public PatientsPatients Patients Patients Patients Patients Alleles Rare Allele AllelesLevel ABCA1 80/630 (12.7%) 113/575 (19.7%) 30/192 (15.6%) 17/165 (10.3%)2/17 (11.8%) 1/5 (20.0%) 0.59 (0.44 to 0.81) 1.61 (0.71 to 3.68) 0.53(0.04 to 7.89) P <= 0.05 ABCA1 80/622 (12.9%) 113/572 (19.8%) 30/190(15.8%) 17/159 (10.7%) 2/16 (12.5%) 1/5 (20.0%) 0.60 (0.44 to 0.83) 1.53(0.80 to 2.91) 0.71 (0.05 to 10.16) P <= 0.05 ADAMTS1 65/470 (13.8%)67/434 (15.4%) 42/305 (13.8%) 51/258 (19.8%) 4/50 (8.0%) 12/42 (28.6%)0.91 (0.62 to 1.32) 0.64 (0.40 to 1.01) 0.20 (0.06 to 0.68) P <= 0.05ADAMTS1 65/471 (13.8%) 67/435 (15.4%) 43/307 (14.0%) 52/258 (20.2%) 4/50(8.0%) 12/42 (28.6%) 0.91 (0.63 to 1.33) 0.63 (0.40 to 0.99) 0.20 (0.06to 0.69) P <= 0.05 AGTR1 50/612 (8.2%) 65/579 (11.2%) 57/521 (10.9%)46/488 (9.4%) 5/100 (5.0%) 20/122 (16.4%) 0.70 (0.48 to 1.04) 1.18 (0.54to 2.56) 0.27 (0.08 to 0.90) P <= 0.05 AGTR1 50/405 (12.3%) 65/364(17.9%) 57/363 (15.7%) 46/299 (15.4%) 5/69 (7.2%) 20/78 (25.6%) 0.65(0.43 to 0.97) 1.02 (0.46 to 2.28) 0.23 (0.07 to 0.79) P <= 0.05 AGTR150/400 (12.5%) 65/361 (18.0%) 57/359 (15.9%) 46/294 (15.6%) 5/67 (7.5%)20/78 (25.6%) 0.65 (0.43 to 0.97) 1.03 (0.66 to 1.58) 0.26 (0.09 to0.74) P <= 0.05 ASAH1 21/201 (10.4%) 43/196 (21.9%) 62/414 (15.0%)67/364 (18.4%) 29/220 (13.2%) 21/181 (11.6%) 0.42 (0.24 to 0.73) 0.78(0.29 to 2.13) 1.16 (0.38 to 3.50) P <= 0.05 CAPG 92/642 (14.3%) 97/559(17.4%) 16/169 (9.5%) 33/160 (20.6%) 3/14 (21.4%) 1/16 (6.3%) 0.81 (0.59to 1.12) 0.37 (0.19 to 0.71) 5.35 (0.44 to 64.87) P <= 0.05 CAPN1070/867 (8.1%) 103/839 (12.3%) 39/333 (11.7%) 25/326 (7.7%) 3/33 (9.1%)3/30 (10.0%) 0.63 (0.46 to 0.86) 1.60 (0.75 to 3.39) 0.90 (0.15 to 5.27)P <= 0.05 CAPN10 70/581 (12.0%) 103/524 (19.7%) 39/230 (17.0%) 25/199(12.6%) 3/26 (11.5%) 3/21 (14.3%) 0.56 (0.40 to 0.78) 1.42 (0.65 to3.09) 0.78 (0.13 to 4.75) P <= 0.05 CAPN10 70/857 (8.2%) 103/828 (12.4%)39/326 (12.0%) 25/316 (7.9%) 3/32 (9.4%) 3/30 (10.0%) 0.62 (0.45 to0.85) 1.58 (0.93 to 2.70) 1.07 (0.19 to 5.86) P <= 0.05 CAPN10 70/574(12.2%) 103/519 (19.8%) 39/227 (17.2%) 25/196 (12.8%) 3/25 (12.0%) 3/21(14.3%) 0.56 (0.40 to 0.79) 1.43 (0.82 to 2.49) 0.90 (0.16 to 5.11) P <=0.05 CAPN2 67/434 (15.4%) 124/442 (28.1%) 60/268 (22.4%) 67/320 (20.9%)10/41 (24.4%) 18/50 (36.0%) 0.46 (0.33 to 0.64) 1.08 (0.73 to 1.60) 0.56(0.22 to 1.42) P <= 0.005 CAPN2 67/386 (17.4%) 124/396 (31.3%) 60/243(24.7%) 67/281 (23.8%) 10/39 (25.6%) 18/41 (43.9%) 0.45 (0.32 to 0.63)1.03 (0.69 to 1.54) 0.43 (0.17 to 1.11) P <= 0.05 CCL11 95/507 (18.7%)145/554 (26.2%) 33/209 (15.8%) 65/238 (27.3%) 7/24 (29.2%) 1/21 (4.8%)0.63 (0.47 to 0.85) 0.50 (0.31 to 0.80) 8.57 (0.95 to 77.17) P <= 0.05CCL11 95/452 (21.0%) 145/491 (29.5%) 33/192 (17.2%) 65/209 (31.1%) 7/19(36.8%) 1/18 (5.6%) 0.62 (0.46 to 0.83) 0.46 (0.29 to 0.75) 9.95 (1.07to 92.24) P <= 0.05 CD163 99/964 (10.3%) 99/936 (10.6%) 10/245 (4.1%)31/246 (12.6%) 3/25 (12.0%) 1/14 (7.1%) 0.97 (0.72 to 1.30) 0.30 (0.12to 0.72) 1.77 (0.16 to 19.92) P <= 0.05 CD163 99/649 (15.3%) 99/573(17.3%) 10/168 (6.0%) 31/166 (18.7%) 3/20 (15.0%) 1/6 (16.7%) 0.86 (0.64to 1.17) 0.28 (0.11 to 0.69) 0.88 (0.07 to 11.07) P <= 0.05 CD163 99/949(10.4%) 99/917 (10.8%) 10/243 (4.1%) 31/243 (12.8%) 3/24 (12.5%) 1/14(7.1%) 0.96 (0.72 to 1.30) 0.29 (0.14 to 0.60) 1.97 (0.18 to 21.69) P <=0.05 CD163 99/640 (15.5%) 99/565 (17.5%) 10/1 66 (6.0%) 31/165 (18.8%)3/20 (15.0%) 1/6 (16.7%) 0.88 (0.64 to 1.20) 0.27 (0.13 to 0.57) 0.99(0.08 to 12.46) P <= 0.05 CD6 68/668 (10.2%) 73/697 (10.5%) 43/470(9.1%) 48/432 (11.1%) 1/92 (1.1%) 10/64 (15.6%) 0.97 (0.68 to 1.37) 0.81(0.38 to 1.69) 0.06 (0.01 to 0.52) P <= 0.05 CD6 68/449 (15.1%) 73/434(16.8%) 43/323 (13.3%) 48/272 (17.6%) 1/63 (1.6%) 10/37 (27.0%) 0.88(0.62 to 1.27) 0.72 (0.33 to 1.54) 0.04 (0.00 to 0.39) P <= 0.05 CD668/656 (10.4%) 73/683 (10.7%) 43/465 (9.2%) 48/426 (11.3%) 1/91 (1.1%)10/62 (16.1%) 0.97 (0.68 to 1.38) 0.80 (0.51 to 1.23) 0.06 (0.01 to0.44) P <= 0.05 CD6 68/442 (15.4%) 73/427 (17.1%) 43/320 (13.4%) 48/270(17.8%) 1/62 (1.6%) 10/37 (27.0%) 0.92 (0.64 to 1.32) 0.68 (0.43 to1.08) 0.04 (0.01 to 0.36) P <= 0.05 CD6 59/792 (7.4%) 89/730 (12.2%)48/392 (12.2%) 37/406 (9.1%) 5/49 (10.2%) 5/53 (9.4%) 0.58 (0.41 to0.82) 1.39 (0.67 to 2.91) 1.09 (0.26 to 4.55) P <= 0.05 CD6 59/549(10.7%) 89/463 (19.2%) 48/261 (18.4%) 37/246 (15.0%) 5/28 (17.9%) 5/32(15.6%) 0.51 (0.35 to 0.72) 1.27 (0.59 to 2.73) 1.17 (0.27 to 5.18) P <=0.05 CD6 59/785 (7.5%) 89/721 (12.3%) 48/381 (12.6%) 37/394 (9.4%) 5/49(10.2%) 5/52 (9.6%) 0.57 (0.41 to 0.81) 1.39 (0.88 to 2.21) 1.09 (0.29to 4.08) P <= 0.05 CD6 59/545 (10.8%) 89/461 (19.3%) 48/254 (18.9%)37/240 (15.4%) 5/28 (17.9%) 5/31 (16.1%) 0.49 (0.34 to 0.70) 1.36 (0.84to 2.20) 1.44 (0.36 to 5.77) P <= 0.005 COL6A2 29/194 (14.9%) 65/217(30.0%) 69/382 (18.1%) 102/395 (25.8%) 38/165 (23.0%) 43/201 (21.4%)0.39 (0.24 to 0.65) 0.62 (0.44 to 0.88) 1.09 (0.66 to 1.79) P <= 0.05COL6A2 29/174 (16.7%) 65/199 (32.7%) 39/343 (20.1%) 102/345 (29.6%)38/148 (25.7%) 43/175 (24.6%) 0.39 (0.24 to 0.65) 0.59 (0.42 to 0.84)1.04 (0.63 to 1.73) P <= 0.05 CR1 111/1177 (9.4%) 122/1143 (10.7%) 1/58(1.7%) 9/52 (17.3%) 0/0 (0.0%) 0/0 (0.0%) 0.87 (0.66 to 1.14) 0.08 (0.01to 0.72 P <= 0.05 CR1 111/802 (13.8%) 122/715 (17.1%) 1/36 (2.8%) 9/29(31.0%) 0/0 (0.0%) 0/0 (0.0%) 0.78 (0.59 to 1.03) 0.06 (0.01 to 0.57) P<= 0.05 CR1 111/1159 (9.6%) 122/1122 (10.9%) 1/58 (1.7%) 9/51 (17.6%)0/0 (0.0%) 0/0 (0.0%) 0.86 (0.65 to 1.13) 0.09 (0.01 to 0.71) P <= 0.05CR1 111/791 (14.0%) 122/706 (17.3%) 1/36 (2.8%) 9/29 (31.0%) 0/0 (0.0%)0/0 (0.0%) 0.78 (0.59 to 1.04) 0.07 (0.01 to 0.57) P <= 0.05 CXCL1626/260 (10.0%) 52/231 (22.5%) 58/411 (14.1%) 56/369 (15.2%) 27/157(17.2%) 23/140 (16.4%) 0.38 (0.23 to 0.64) 0.92 (0.36 to 2.33) 1.06(0.37 to 2.99) P <= 0.05 CXCL16 26/256 (10.2%) 52/229 (22.7%) 58/406(14.3%) 56/364 (15.4%) 27/155 (17.4%) 23/138 (16.7%) 0.38 (0.23 to 0.64)0.91 (0.61 to 1.37) 1.12 (0.60 to 2.08) P <= 0.05 ELN 32/294 (10.9%)48/252 (19.0%) 55/409 (13.4%) 65/362 (18.0%) 24/132 (18.2%) 15/123(12.2%) 0.52 (0.32 to 0.84) 0.71 (0.29 to 1.75) 1.60 (0.55 to 4.68) P <=0.05 ELN 32/291 (11.0%) 48/248 (19.4%) 55/402 (13.7%) 65/359 (18.1%)24/131 (17.3%) 15/121 (12.4%) 0.53 (0.32 to 0.87) 0.70 (0.47 to 1.05)1.64 (0.80 to 3.32) P <= 0.05 FCAR 103/734 (14.0%) 104/637 (16.3%) 8/96(8.3%) 26/103 (25.2%) 1/8 (12.5%) 1/4 (25.0%) 0.84 (0.62 to 1.12) 0.27(0.10 to 0.73) 0.43 (0.02 to 9.77) P <= 0.05 FGB 95/512 (18.6%) 147/566(26.0%) 33/209 (15.8%) 57/219 (26.0%) 8/16 (50.0%) 6/24 (25.0%) 0.63(0.47 to 0.85) 0.52 (0.32 to 0.84) 3.14 (0.81 to 12.11) P <= 0.05 GALC87/581 (15.0%) 84/532 (15.8%) 20/207 (9.7%) 29/178 (21.9%) 5/34 (14.7%)2/15 (13.3%) 0.94 (0.68 to 1.30) 0.38 (0.17 to 0.86) 1.12 (0.18 to 7.16)P <= 0.05 GAPD 75/454 (16.5%) 148/534 (27.7%) 52/260 (20.0%) 54/244(22.1%) 10/26 (38.5%) 9/32 (28.1%) 0.50 (0.37 to 0.69) 0.88 (0.57 to1.35) 1.56 (0.52 to 4.69) P <= 0.05 GAPD 75/415 (18.1%) 148/466 (31.8%)52/227 (22.9%) 54/217 (24.9%) 10/23 (43.5%) 9/32 (28.1%) 0.46 (0.34 to0.64) 0.89 (0.57 to 1.37) 1.92 (0.62 to 5.93) P <= 0.05 HLA-DPB1 46/606(7.6%) 71/585 (12.1%) 49/514 (9.5%) 56/505 (11.1%) 17/110 (15.5%) 4/98(4.1%) 0.59 (0.40 to 0.88) 0.84 (0.39 to 1.82) 4.29 (1.17 to 15.78) P <=0.05 HLA-DPB1 46/416 (11.1%) 71/370 (19.2%) 49/354 (14.2%) 56/300(18.7%) 17/77 (22.1%) 4/69 (5.8%) 0.52 (0.35 to 0.78) 0.72 (0.33 to1.60) 4.60 (1.22 to 17.36) P <= 0.005 HLA-DPB1 46/598 (7.7%) 71/578(12.3%) 49/504 (9.7%) 56/492 (11.4%) 17/110 (15.5%) 4/96 (4.2%) 0.59(0.39 to 0.87) 0.84 (0.56 to 1.27) 4.39 (1.42 to 13.62) P <= 0.05HLA-DPB1 46/410 (11.2%) 71/368 (19.3%) 49/340 (14.4%) 56/295 (19.0%)17/77 (22.1%) 4/67 (6.0%) 0.51 (0.34 to 0.76) 0.75 (0.49 to 1.15) 4.91(1.54 to 15.64) P <= 0.005 HLA-DPB1 48/643 (7.5%) 72/629 (11.4%) 51/502(10.2%) 56/480 (11.7%) 13/88 (14.8%) 3/87 (3.4%) 0.62 (0.43 to 0.92)0.86 (0.40 to 1.83) 4.85 (1.14 to 20.58) P <= 0.05 HLA-DPB1 48/438(11.0%) 72/391 (18.4%) 51/336 (15.2%) 56/294 (19.0%) 13/63 (20.6%) 3/60(5.0%) 0.55 (0.37 to 0.81) 0.76 (0.35 to 1.67) 4.94 (1.14 to 21.49) P <=0.05 HLA-DPB1 48/636 (7.5%) 72/620 (11.6%) 51/491 (10.4%) 56/469 (11.9%)13/88 (14.8%) 3/85 (3.5%) 0.60 (0.41 to 0.89) 0.87 (0.58 to 1.31) 5.02(1.37 to 18.44) P <= 0.05 HLA-DPB1 48/432 (11.1%) 72/389 (18.5%) 51/331(15.4%) 56/289 (19.4%) 13/63 (20.6%) 3/58 (5.2%) 0.52 (0.35 to 0.78)0.80 (0.52 to 1.23) 5.41 (1.43 to 20.48) P <= 0.005 HLA-DPB1 68/544(12.5%) 90/474 (19.0%) 37/263 (14.1%) 39/234 (16.7%) 7/31 (22.3%) 2/35(5.7%) 0.61 (0.43 to 0.86) 0.82 (0.38 to 1.75) 4.81 (0.83 to 27.84) P <=0.05 HLA-DPB1 68/536 (12.7%) 90/472 (19.1%) 37/260 (14.2%) 39/228(17.1%) 7/31 (22.6%) 2/34 (5.9%) 0.60 (0.42 to 0.85) 0.84 (0.51 to 1.38)5.83 (1.08 to 31.55) P <= 0.05 HLA-DPB1 61/510 (12.0%) 86/452 (19.0%)43/294 (14.6%) 41/245 (16.7%) 8/35 (22.9%) 3/45 (6.7%) 0.58 (0.41 to0.83) 0.85 (0.40 to 1.83) 4.15 (0.89 to 19.26) P <= 0.05 HLA-DPB1 61/502(12.2%) 86/450 (19.1%) 43/291 (14.8%) 41/240 (17.1%) 8/35 (22.9%) 3/43(7.0%) 0.57 (0.40 to 0.82) 0.87 (0.54 to 1.41) 4.69 (1.11 to 19.80) P <=0.05 HLA-DQB1 85/840 (10.1%) 86/840 (10.2%) 22/361 (6.1%) 42/314 (13.4%)5/35 (14.3%) 3/40 (7.5%) 0.99 (0.72 to 1.35) 0.42 (0.19 to 0.91) 2.06(0.41 to 10.25) P <= 0.05 HLA-DQB1 85/576 (14.8%) 86/520 (16.5%) 22/241(9.1%) 42/199 (21.1%) 5/22 (22.7%) 3/25 (12.0%) 0.87 (0.63 to 1.21) 0.38(0.17 to 0.83) 2.16 (0.41 to 11.39) P <= 0.05 HLA-DQB1 85/827 (10.3%)86/825 (10.4%) 22/356 (6.2%) 42/308 (13.6%) 5/35 (14.3%) 3/40 (7.5%)0.99 (0.72 to 1.37) 0.40 (0.23 to 0.70) 2.00 (0.44 to 9.18) P <= 0.05HLA-DQB1 85/566 (15.0%) 86/513 (16.8%) 22/240 (9.2%) 42/198 (21.2%) 5/22(22.7%) 3/25 (12.0%) 0.90 (0.64 to 1.25) 0.36 (0.20 to 0.63) 2.22 (0.45to 10.95) P <= 0.05 HRC 54/253 (21.3%) 60/247 (24.3%) 51/361 (14.1%)113/402 (28.1%) 30/127 (23.6%) 37/164 (22.6%) 0.85 (0.56 to 1.29) 0.41(0.28 to 0.59) 1.04 (0.60 to 1.81) P <= 0.05 HRC 54/229 (23.6%) 60/216(27.8%) 51/324 (15.7%) 113/357 (31.7%) 30/113 (26.5%) 37/146 (25.3%)0.80 (0.52 to 1.23) 0.39 (0.27 to 0.57) 1.05 (0.60 to 1.84) P <= 0.005IL1A 62/370 (16.8%) 121/400 (30.3%) 64/306 (20.9%) 78/351 (22.2%) 11/60(18.3%) 11/61 (18.0%) 0.46 (0.32 to 0.65) 0.91 (0.63 to 1.33) 0.94 (0.37to 2.38) P <= 0.05 IL1A 62/324 (19.1%) 121/354 (34.2%) 64/281 (22.8%)78/307 (25.4%) 11/54 (20.4%) 11/56 (19.6%) 0.45 (0.31 to 0.64) 0.85(0.58 to 1.25) 0.98 (0.38 to 2.51) P <= 0.05 IL1RN 67/454 (14.8%) 70/393(17.8%) 32/325 (9.8%) 53/277 (19.1%) 12/58 (20.7%) 8/67 (11.9%) 0.80(0.55 to 1.15) 0.46 (0.21 to 1.02) 1.92 (0.60 to 6.15) P <= 0.05 IL1RN67/446 (15.0%) 70/387 (18.1%) 32/323 (9.9%) 53/276 (19.2%) 12/57 (21.1%)8/66 (12.1%) 0.77 (0.53 to 1.12) 0.50 (0.31 to 0.80) 1.97 (0.73 to 5.31)P <= 0.05 IL4R 25/346 (7.2%) 42/361 (11.6%) 60/589 (10.2%) 73/557(13.1%) 27/280 (9.6%) 16/252 (6.3%) 0.58 (0.34 to 0.97) 0.74 (0.51 to1.07) 1.66 (0.87 to 3.18) P <= 0.05 IL4R 25/218 (11.5%) 42/230 (18.3%)60/415 (14.5%) 73/354 (20.6%) 27/193 (14.0%) 16/149 (10.7%) 0.57 (0.33to 0.97) 0.64 (0.43 to 0.93) 1.52 (0.78 to 2.96) P <= 0.05 ITGAE 57/381(15.0%) 57/313 (18.2%) 48/360 (13.3%) 55/349 (15.8%) 7/87 (8.0%) 19/72(26.4%) 0.79 (0.53 to 1.20) 0.84 (0.55 to 1.28) 0.24 (0.09 to 0.61) P <=0.05 KDR 78/666 (11.7%) 107/597 (17.9%) 33/162 (20.4%) 21/137 (15.3%)1/10 (10.0%) 3/11 (27.3%) 0.61 (0.44 to 0.83) 1.41 (0.63 to 3.16) 0.30(0.02 to 3.66) P <= 0.05 KDR 78/975 (8.0%) 107/946 (11.3%) 33/227(14.5%) 21/208 (10.1%) 1/15 (6.7%) 3/18 (16.7%) 0.66 (0.49 to 0.90) 1.68(0.93 to 3.04) 0.41 (0.04 to 4.50) P <= 0.05 KDR 78/660 (11.8%) 107/591(18.1%) 33/157 (21.0%) 21/134 (15.7%) 1/10 (10.0%) 3/11 (27.3%) 0.58(0.42 to 0.81) 1.68 (0.91 to 3.11) 0.35 (0.03 to 4.21) P <= 0.05 KDR78/665 (11.7%) 106/594 (17.8%) 33/161 (20.5%) 21/136 (15.4%) 1/11 (9.1%)3/11 (27.3%) 0.61 (0.45 to 0.84) 1.41 (0.63 to 3.16) 0.27 (0.02 to 3.26)P <= 0.05 KDR 78/973 (8.0%) 106/943 (11.2%) 33/226 (14.6%) 21/208(10.1%) 1/16 (6.3%) 3/18 (16.7%) 0.67 (0.49 to 0.91) 1.69 (0.94 to 3.06)0.38 (0.03 to 4.17) P <= 0.05 KDR 78/659 (11.8%) 106/588 (18.0%) 33/156(21.2%) 21/134 (15.7%) 1/11 (9.1%) 3/11 (27.3%) 0.59 (0.42 to 0.81) 1.69(0.91 to 3.13) 0.31 (0.03 to 3.71) P <= 0.05 KLK14 52/560 (9.3%) 50/560(8.9%) 54/556 (9.7%) 57/511 (11.2%) 6/114 (5.3%) 23/115 (20.0%) 1.04(0.69 to 1.57) 0.86 (0.38 to 1.92) 0.22 (0.07 to 0.72) P <= 0.05 KLK1452/366 (14.2%) 50/342 (14.6%) 54/401 (13.5%) 57/323 (17.6%) 6/67 (9.0%)23/76 (30.3%) 0.97 (0.64 to 1.47) 0.73 (0.32 to 1.67) 0.23 (0.07 to0.76) P <= 0.05 KLK14 52/550 (9.5%) 50/549 (9.1%) 54/549 (9.8%) 57/502(11.4%) 6/113 (5.3%) 23/113 (20.4%) 1.02 (0.68 to 1.54) 0.85 (0.57 to1.27) 0.23 (0.09 to 0.60) P <= 0.05 KLK14 52/359 (14.5%) 50/339 (14.7%)54/397 (13.6%) 57/318 (17.9%) 6/67 (9.0%) 23/75 (30.7%) 0.98 (0.64 to1.50) 0.74 (0.49 to 1.12) 0.23 (0.09 to 0.62) P <= 0.05 LRP3 115/552(20.8%) 158/621 (25.4%) 19/172 (11.0%) 52/176 (29.5%) 3/11 (27.3%) 2/15(13.3%) 0.76 (0.58 to 1.00) 0.29 (0.16 to 0.51) 2.40 (0.32 to 17.85) P<= 0.005 LRP3 115/491 (23.4%) 158/550 (28.7%) 19/158 (12.0%) 52/156(33.3%) 3/11 (27.3%) 2/12 (16.7%) 0.75 (0.57 to 0.99) 0.26 (0.15 to0.47) 1.80 (0.24 to 13.73) P <= 0.005 MICA 79/608 (13.0%) 99/549 (18.0%)27/204 (13.2%) 30/168 (17.9%) 6/16 (37.5%) 2/18 (11.1%) 0.67 (0.48 to0.93) 0.72 (0.40 to 1.27) 6.64 (1.06 to 41.59) P <= 0.05 MYH7 105/1200(8.8%) 130/1144 (11.4%) 7/31 (22.6%) 1/47 (2.1%) 0/0 (0.0%) 0/0 (0.0%)0.75 (0.57 to 0.98) 13.41 (1.48 to 121.25) P <= 0.05 MYH7 105/816(12.9%) 130/715 (18.2%) 7/20 (35.0%) 1/27 (3.7%) 0/0 (0.0%) 0/0 (0.0%)0.66 (0.50 to 0.88) 14.00 (1.48 to 132.80) P <= 0.05 MYH7 105/1182(8.9%) 130/1124 (11.6%) 7/31 (22.6%) 1/45 (2.2%) 0/0 (0.0%) 0/0 (0.0%)0.75 (0.57 to 0.98) 12.05 (1.39 to 104.59) P <= 0.005 MYH7 105/805(13.0%) 130/707 (18.4%) 7/20 (35.0%) 1/26 (3.8%) 0/0 (0.0%) 0/0 (0.0%)0.67 (0.51 to 0.90) 11.70 (1.28 to 107.21) P <= 0.005 NOS3 46/539 (8.5%)56/528 (10.6%) 60/527 (11.4%) 58/526 (11.0%) 6/169 (3.6%) 17/140 (12.1%)0.79 (0.52 to 1.18) 1.04 (0.47 to 2.30) 0.27 (0.08 to 0.87) P <= 0.05NOS3 46/361 (12.7%) 56/325 (17.2%) 60/362 (16.6%) 58/335 (17.3%) 6/115(5.2%) 17/85 (20.0%) 0.70 (0.46 to 1.07) 0.95 (0.42 to 2.16) 0.22 (0.07to 0.74) P <= 0.05 NOS3 46/532 (8.6%) 56/516 (10.9%) 60/521 (11.5%)58/521 (11.1%) 6/164 (3.7%) 17/135 (12.6%) 0.76 (0.50 to 1.16) 1.04(0.71 to 1.54) 0.27 (0.10 to 0.70) P <= 0.05 NOS3 46/355 (13.0%) 56/318(17.6%) 60/359 (16.7%) 58/333 (17.4%) 6/113 (5.3%) 17/85 (20.0%) 0.67(0.44 to 1.04) 0.98 (0.66 to 1.47) 0.23 (0.09 to 0.63) P <= 0.05 NPC148/462 (10.4%) 37/436 (8.5%) 46/552 (8.3%) 65/575 (11.3%) 18/208 (8.7%)28/173 (16.2%) 1.25 (0.80 to 1.96) 0.71 (0.29 to 1.74) 0.49 (0.18 to1.35) P <= 0.05 NPC1 48/302 (15.9%) 37/282 (13.1%) 46/381 (12.1%) 65/360(18.1%) 18/146 (12.3%) 28/95 (29.5%) 1.25 (0.79 to 1.99) 0.62 (0.25 to1.55) 0.34 (0.12 to 0.96) P <= 0.005 NPC1 48/299 (16.1%) 37/279 (13.3%)46/376 (12.2%) 65/356 (18.3%) 18/143 (12.6%) 28/93 (30.1%) 1.21 (0.76 to1.94) 0.65 (0.43 to 0.98) 0.34 (0.17 to 0.67) P <= 0.05 PLAB 72/706(10.2%) 67/675 (9.9%) 34/455 (7.5%) 60/443 (13.5%) 6/72 (8.3%) 4/75(5.3%) 1.03 (0.73 to 1.46) 0.52 (0.24 to 1.10) 1.61 (0.38 to 6.84) P <=0.05 PLAB 72/478 (15.1%) 67/417 (16.1%) 34/303 (11.2%) 60/280 (21.4%)6/57 (10.5%) 4/46 (8.7%) 0.93 (0.64 to 1.33) 0.46 (0.21 to 1.01) 1.24(0.28 to 5.38) P <= 0.05 PLAB 72/694 (10.4%) 67/660 (10.2%) 34/449(7.6%) 60/439 (13.7%) 6/72 (8.3%) 4/73 (5.5%) 1.03 (0.73 to 1.47) 0.50(0.32 to 0.79) 1.62 (0.43 to 6.05) P <= 0.05 PLAB 72/471 (15.3%) 67/411(16.3%) 34/299 (11.4%) 60/278 (21.6%) 6/57 (10.5%) 4/46 (8.7%) 0.95(0.66 to 1.37) 0.44 (0.28 to 0.71) 1.45 (0.38 to 5.57) P <= 0.05 PRKCQ50/655 (7.6%) 83/657 (12.6%) 51/471 (10.8%) 45/445 (10.1%) 11/100(11.0%) 3/85 (3.5%) 0.57 (0.40 to 0.83) 1.08 (0.51 to 2.28) 3.38 (0.79to 14.38) P <= 0.05 PRKCQ 50/425 (11.8%) 83/434 (19.1%) 51/343 (14.9%)45/264 (17.0%) 11/62 (17.7%) 3/42 (7.1%) 0.56 (0.39 to 0.82) 0.85 (0.39to 1.84) 2.80 (0.63 to 12.38) P <= 0.05 PRKCQ 50/645 (7.8%) 83/645(12.9%) 51/465 (11.0%) 45/437 (10.3%) 11/98 (11.2%) 3/83 (3.6%) 0.58(0.40 to 0.84) 1.04 (0.68 to 1.60) 3.15 (0.84 to 11.74) P <= 0.05SERPINA5 50/557 (9.0%) 56/545 (10.3%) 41/515 (8.0%) 65/515 (12.6%)21/139 (15.1%) 10/111 (9.0%) 0.85 (0.59 to 1.33) 0.57 (0.38 to 0.87)1.72 (0.77 to 3.86) P <= 0.05 SN 33/220 (15.0%) 38/194 (19.6%) 66/443(14.9%) 58/382 (15.2%) 13/174 (7.5%) 35/168 (20.8%) 0.72 (0.43 to 1.21)0.98 (0.37 to 2.56) 0.31 (0.10 to 0.93) P <= 0.05 SN 33/214 (15.4%)38/193 (19.7%) 66/439 (15.0%) 58/378 (15.3%) 13/173 (7.5%) 35/164(21.3%) 0.71 (0.42 to 1.19) 1.02 (0.69 to 1.51) 0.30 (0.15 to 0.60) P <=0.05 TAP1 83/848 (9.8%) 81/829 (9.8%) 28/349 (8.0%) 42/329 (12.8%) 1/36(2.8%) 8/33 (24.2%) 1.00 (0.73 to 1.38) 0.60 (0.28 to 1.27) 0.09 (0.01to 0.82) P <= 0.05 TAP1 83/576 (14.4%) 81/505 (16.0%) 28/237 (11.8%)42/214 (19.6%) 1/25 (4.0%) 8/24 (33.3%) 0.88 (0.63 to 1.23) 0.55 (0.25to 1.19) 0.08 (0.01 to 0.79) P <= 0.05 TAP1 83/832 (10.0%) 81/817 (9.9%)28/347 (8.1%) 42/319 (13.2%) 1/36 (2.8%) 8/33 (24.2%) 0.98 (0.71 to1.36) 0.61 (0.37 to 1.01) 0.08 (0.01 to 0.70) P <= 0.05 TAP1 83/566(14.7%) 81/501 (16.2%) 28/236 (11.9%) 42/209 (20.1%) 1/25 (4.0%) 8/24(33.3%) 0.89 (0.63 to 1.25) 0.56 (0.33 to 0.94) 0.08 (0.01 to 0.72) P <=0.05 TIMP2 75/561 (13.4%) 85/513 (16.6%) 30/234 (12.8%) 44/200 (22.0%)7/24 (29.2%) 1/17 (5.9%) 0.76 (0.64 to 1.08) 0.56 (0.33 to 0.93) 6.81(0.74 to 62.66) P <= 0.05 TNF 85/579 (14.7%) 86/524 (16.4%) 24/223(10.8%) 41/211 (19.4%) 3/35 (8.6%) 4/9 (44.4%) 0.88 (0.63 to 1.21) 0.50(0.23 to 1.10) 0.12 (0.02 to 0.75) P <= 0.05 TNF 85/573 (14.8%) 86/517(16.6%) 24/219 (11.0%) 41/209 (19.6%) 3/34 (8.8%) 4/9 (44.4%) 0.87 (0.62to 1.22) 0.52 (0.30 to 0.90) 0.14 (0.02 to 0.81) P <= 0.05 VTN 35/340(10.3%) 25/361 (6.9%) 56/629 (8.9%) 74/567 (13.1%) 21/266 (7.9%) 32/268(11.9%) 1.54 (0.90 to 2.64) 0.65 (0.23 to 1.81) 0.63 (0.21 to 1.93) P <=0.05 VTN 35/236 (14.8%) 25/213 (11.7%) 56/428 (13.1%) 74/357 (20.7%)21/174 (12.1%) 32/175 (18.3%) 1.31 (0.76 to 2.27) 0.58 (0.20 to 1.64)0.61 (0.20 to 1.93) P <= 0.05 VTN 35/337 (10.4%) 25/352 (7.1%) 56/620(9.0%) 74/559 (13.2%) 21/260 (8.1%) 32/263 (12.2%) 1.51 (0.88 to 2.59)0.63 (0.43 to 0.91) 0.66 (0.37 to 1.19) P <= 0.05 VTN 35/235 (14.9%)25/210 (11.9%) 56/424 (13.2%) 74/352 (21.0%) 21/168 (12.5%) 32/174(18.4%) 1.37 (0.78 to 2.42) 0.56 (0.38 to 0.82) 0.64 (0.35 to 1.18) P <=0.05 A2M 42/525 (8.0%) 64/479 (13.4%) 72/540 (13.3%) 72/544 (13.2%)11/144 (7.6%) 20/138 (14.5%) 0.55 (0.36 to 0.83) 1.04 (0.73 to 1.48)0.47 (0.21 to 1.02) P <= 0.05 A2M 42/355 (11.8%) 64/318 (20.1%) 72/380(18.9%) 72/351 (20.5%) 11/101 (10.9%) 20/86 (23.3%) 0.53 (0.34 to 0.81)0.93 (0.65 to 1.35) 0.38 (0.17 to 0.86) P <= 0.05 ABCA1 56/625 (9.0%)96/628 (15.3%) 59/517 (11.4%) 56/487 (11.5%) 12/94 (12.8%) 6/80 (7.5%)0.55 (0.38 to 0.77) 0.99 (0.49 to 2.00) 1.80 (0.55 to 5.89) P <= 0.05ABCA1 56/414 (13.5%) 96/414 (23.2%) 59/375 (15.7%) 56/304 (18.4%) 12/65(18.5%) 6/54 (11.1%) 0.52 (0.36 to 0.74) 0.83 (0.40 to 1.71) 1.81 (0.54to 6.11) P <= 0.05 ABCA1 56/612 (9.2%) 96/616 (15.6%) 59/509 (11.6%)56/478 (11.7%) 12/93 (12.9%) 6/77 (7.8%) 0.55 (0.38 to 0.78) 0.98 (0.66to 1.46) 1.71 (0.61 to 4.83) P <= 0.05 ABCA1 56/405 (13.8%) 96/410(23.4%) 59/371 (15.9%) 56/298 (18.8%) 12/64 (18.8%) 6/53 (11.3%) 0.52(0.36 to 0.76) 0.82 (0.54 to 1.24) 1.81 (0.62 to 5.28) P <= 0.05 ABCA192/931 (9.9%) 137/927 (14.8%) 31/282 (11.0%) 19/253 (7.5%) 4/23 (17.4%)1/14 (7.1%) 0.63 (0.48 to 0.84) 1.52 (0.71 to 3.26) 2.74 (0.26 to 28.71)P <= 0.05 ABCA1 92/642 (14.3%) 137/599 (22.9%) 31/193 (16.1%) 19/167(11.4%) 4/19 (21.1%) 1/5 (20.0%) 0.56 (0.42 to 0.76) 1.49 (0.68 to 3.27)1.07 (0.09 to 13.02) P <= 0.05 ABCA1 92/913 (10.1%) 137/915 (15.0%)31/279 (11.1%) 19/242 (7.9%) 4/22 (18.2%) 1/13 (7.7%) 0.63 (0.48 to0.84) 1.46 (0.80 to 2.67) 2.99 (0.29 to 30.36) P <= 0.05 ABCA1 92/631(14.6%) 137/595 (23.0%) 31/191 (16.2%) 19/160 (11.9%) 4/18 (22.2%) 1/5(20.0%) 0.57 (0.43 to 0.77) 1.37 (0.73 to 2.55) 1.39 (0.12 to 16.54) P<= 0.05 ADAM12 95/741 (12.8%) 97/728 (13.3%) 25/393 (6.4%) 44/357(12.3%) 7/58 (12.1%) 11/54 (20.4%) 0.98 (0.72 to 1.33) 0.47 (0.28 to0.79) 0.47 (0.17 to 1.33) P <= 0.05 ADAM12 95/525 (18.1%) 97/478 (20.3%)25/260 (9.6%) 44/224 (19.6%) 7/41 (17.1%) 11/36 (30.6%) 0.91 (0.66 to1.25) 0.42 (0.25 to 0.72) 0.37 (0.12 to 1.10) P <= 0.05 ALOX12 48/421(11.4%) 47/411 (11.4%) 64/611 (10.5%) 68/544 (12.5%) 15/198 (7.6%)42/236 (17.8%) 1.00 (0.65 to 1.53) 0.82 (0.36 to 1.87) 0.38 (0.14 to1.00) P <= 0.05 ALOX12 48/418 (11.5%) 47/410 (11.5%) 64/616 (10.4%)69/546 (12.6%) 15/198 (7.6%) 42/236 (17.8%) 1.00 (0.65 to 1.54) 0.80(0.35 to 1.73) 0.38 (0.14 to 1.00) P <= 0.05 C14orf159 63/560 (11.3%)74/517 (14.3%) 57/511 (11.2%) 55/488 (11.3%) 7/140 (5.0%) 24/160 (15.0%)0.76 (0.53 to 1.09) 0.99 (0.48 to 2.05) 0.30 (0.10 to 0.87) P <= 0.05C14orf159 63/551 (11.4%) 74/511 (14.5%) 57/499 (11.4%) 55/475 (11.6%)7/140 (5.0%) 24/156 (15.4%) 0.74 (0.52 to 1.07) 0.99 (0.66 to 1.47) 0.30(0.12 to 0.73) P <= 0.05 CAPN2 80/434 (18.4%) 132/442 (29.9%) 70/268(26.1%) 78/320 (24.4%) 10/41 (24.4%) 21/50 (42.0%) 0.52 (0.38 to 0.72)1.07 (0.73 to 1.55) 0.46 (0.18 to 1.13) P <= 0.05 CAPN2 80/399 (20.1%)132/404 (32.7%) 70/253 (27.7%) 78/292 (26.7%) 10/39 (25.6%) 21/44(47.7%) 0.51 (0.37 to 0.70) 1.02 (0.70 to 1.50) 0.38 (0.15 to 0.98) P <=0.05 CCL11 107/507 (21.1%) 155/554 (28.0%) 43/209 (20.6%) 75/238 (31.5%)10/24 (41.7%) 2/21 (9.5%) 0.67 (0.50 to 0.89) 0.57 (0.37 to 0.88) 6.96(1.31 to 37.07) P <= 0.05 CCL11 107/464 (23.1%) 155/501 (30.9%) 43/202(21.3%) 75/219 (34.2%) 10/22 (45.5%) 2/19 (10.5%) 0.65 (0.49 to 0.87)0.53 (0.34 to 0.82) 7.20 (1.32 to 39.14) P <= 0.005 CD163 111/964(11.5%) 119/936 (12.7%) 12/245 (4.9%) 37/246 (15.0%) 4/25 (16.0%) 2/14(14.3%) 0.89 (0.68 to 1.18) 0.29 (0.13 to 0.67) 1.14 (0.17 to 7.64) P <=0.05 CD163 111/661 (16.8%) 119/593 (20.1%) 12/170 (7.1%) 37/172 (21.5%)4/21 (19.0%) 2/7 (28.6%) 0.80 (0.60 to 1.07) 0.28 (0.12 to 0.65) 0.59(0.08 to 4.48) P <= 0.05 CD163 111/946 (11.7%) 119/915 (13.0%) 12/242(5.0%) 37/243 (15.2%) 4/24 (16.7%) 2/14 (14.3%) 0.89 (0.67 to 1.18) 0.28(0.14 to 0.56) 1.23 (0.19 to 7.95) P <= 0.05 CD163 111/650 (17.1%)119/583 (20.4%) 12/167 (7.2%) 37/171 (21.6%) 4/21 (19.0%) 2/7 (28.6%)0.82 (0.61 to 1.09) 0.27 (0.13 to 0.54) 0.64 (0.09 to 4.75) P <= 0.05CD6 77/668 (11.5%) 89/697 (12.8%) 48/470 (10.2%) 59/432 (13.7%) 2/92(2.2%) 10/64 (15.6%) 0.89 (0.64 to 1.23) 0.72 (0.36 to 1.43) 0.12 (0.02to 0.63) P <= 0.05 CD6 77/458 (16.8%) 89/450 (19.8%) 48/328 (14.6%)59/283 (20.8%) 2/64 (3.1%) 10/37 (27.0%) 0.82 (0.59 to 1.15) 0.65 (0.32to 1.33) 0.09 (0.02 to 0.47) P <= 0.05 CD6 77/654 (11.8%) 89/682 (13.0%)48/463 (10.4%) 59/425 (13.9%) 2/91 (2.2%) 10/62 (16.1%) 0.89 (0.64 to1.23) 0.71 (0.47 to 1.07) 0.12 (0.02 to 0.55) P <= 0.05 CD6 77/449(17.1%) 89/442 (20.1%) 48/324 (14.8%) 59/280 (21.1%) 2/63 (3.2%) 10/37(27.0%) 0.84 (0.59 to 1.18) 0.63 (0.41 to 0.97) 0.09 (0.02 to 0.42) P <=0.05 COL11A1 95/815 (11.7%) 96/768 (12.5%) 30/332 (9.0%) 49/332 (14.8%)1/52 (1.9%) 7/51 (13.7%) 0.92 (0.68 to 1.25) 0.57 (0.35 to 0.93) 0.11(0.01 to 0.95) P <= 0.05 COL2A1 92/583 (15.8%) 114/526 (21.7%) 27/233(11.6%) 40/215 (18.6%) 7/20 (35.0%) 1/14 (7.1%) 0.66 (0.49 to 0.91) 0.60(0.35 to 1.02) 7.20 (0.77 to 67.69) P <= 0.05 CR1 125/1177 (10.6%)147/1143 (12.9%) 2/58 (3.4%) 11/52 (21.2%) 0/0 (0.0%) 0/0 (0.0%) 0.81(0.62 to 1.04) 0.13 (0.03 to 0.67) P <= 0.05 CR1 125/816 (15.3%) 147/740(19.9%) 2/37 (5.4%) 11/31 (35.5%) 0/0 (0.0%) 0/0 (0.0%) 0.73 (0.56 to0.95) 0.10 (0.02 to 0.55) P <= 0.05 CR1 125/1155 (10.8%) 147/1120(13.1%) 2/58 (3.4%) 11/51 (21.6%) 0/0 (0.0%) 0/0 (0.0%) 0.80 (0.62 to1.03) 0.13 (0.03 to 0.62) P <= 0.05 CR1 125/802 (15.6%) 147/729 (20.2%)2/37 (5.4%) 11/31 (35.5%) 0/0 (0.0%) 0/0 (0.0%) 0.73 (0.56 to 0.95) 0.11(0.02 to 0.53) P <= 0.05 CXCL16 26/376 (6.9%) 58/380 (15.3%) 68/611(11.1%) 74/584 (12.7%) 32/237 (13.5%) 26/223 (11.7%) 0.41 (0.25 to 0.67)0.86 (0.36 to 2.06) 1.18 (0.45 to 3.11) P <= 0.05 CXCL16 26/260 (10.0%)58/237 (24.5%) 68/421 (16.2%) 74/387 (19.1%) 32/162 (19.8%) 26/143(18.2%) 0.34 (0.21 to 0.57) 0.81 (0.33 to 2.00) 1.11 (0.41 to 3.03) P <=0.005 CXCL16 26/369 (7.0%) 58/373 (15.5%) 68/600 (11.3%) 74/573 (12.9%)32/233 (13.7%) 26/217 (12.0%) 0.41 (0.25 to 0.67) 0.85 (0.60 to 1.22)1.17 (0.67 to 2.04) P <= 0.05 CXCL16 26/255 (10.2%) 58/234 (24.8%)68/414 (16.4%) 74/382 (19.4%) 32/160 (20.0%) 26/140 (18.6%) 0.34 (0.21to 0.57) 0.81 (0.56 to 1.17) 1.14 (0.64 to 2.05) P <= 0.005 CYBA 46/510(9.0%) 75/515 (14.6%) 58/567 (10.2%) 68/525 (13.0%) 23/136 (16.9%)15/132 (11.4%) 0.57 (0.39 to 0.85) 0.77 (0.53 to 1.12) 1.64 (0.81 to3.33) P <= 0.05 DDEF1 35/208 (16.8%) 80/262 (30.5%) 83/368 (22.6%)117/395 (29.6%) 42/167 (25.1%) 36/152 (23.7%) 0.45 (0.29 to 0.71) 0.68(0.49 to 0.95) 1.06 (0.64 to 1.77) P <= 0.05 ELN 39/425 (9.2%) 64/406(15.8%) 60/599 (10.0%) 75/579 (13.0%) 28/208 (13.5%) 16/201 (8.0%) 0.54(0.35 to 0.82) 0.75 (0.34 to 1.66) 1.80 (0.69 to 4.70) P <= 0.05 ELN39/301 (13.0%) 64/268 (23.9%) 60/414 (14.5%) 75/372 (20.2%) 28/136(20.6%) 16/124 (12.9%) 0.47 (0.31 to 0.74) 0.67 (0.29 to 1.53) 1.75(0.65 to 4.73) P <= 0.05 ELN 39/417 (9.4%) 64/394 (16.2%) 60/589 (10.2%)75/571 (13.1%) 28/204 (13.7%) 16/197 (8.1%) 0.52 (0.34 to 0.80) 0.74(0.52 to 1.07) 1.90 (0.99 to 3.65) P <= 0.005 ELN 39/297 (13.1%) 64/263(24.3%) 60/407 (14.7%) 75/369 (20.3%) 28/133 (21.1%) 16/121 (13.2%) 0.48(0.30 to 0.74) 0.66 (0.45 to 0.97) 1.84 (0.93 to 3.64) P <= 0.005 F13A165/694 (9.4%) 92/668 (13.8%) 48/442 (10.9%) 59/426 (13.8%) 14/72 (19.4%)7/73 (9.6%) 0.63 (0.45 to 0.89) 0.78 (0.52 to 1.17) 2.29 (0.86 to 6.12)P <= 0.05 F7 91/978 (9.3%) 133/957 (13.9%) 35/236 (14.8%) 20/208 (9.6%)1/13 (7.7%) 3/18 (16.7%) 0.64 (0.48 to 0.84) 1.64 (0.77 to 3.48) 0.42(0.04 to 4.75) P <= 0.05 F7 91/667 (13.6%) 133/622 (21.4%) 35/170(20.6%) 20/130 (15.4%) 1/9 (11.1%) 3/12 (25.0%) 0.58 (0.43 to 0.78) 1.43(0.65 to 3.11) 0.38 (0.03 to 4.59) P <= 0.05 F7 91/959 (9.5%) 133/937(14.2%) 35/233 (15.0%) 20/204 (9.8%) 1/13 (7.7%) 3/18 (16.7%) 0.63 (0.48to 0.84) 1.58 (0.87 to 2.84) 0.51 (0.05 to 5.64) P <= 0.05 F7 91/655(13.9%) 133/613 (21.7%) 35/168 (20.8%) 20/128 (15.6%) 1/9 (11.1%) 3/12(25.0%) 0.59 (0.44 to 0.79) 1.37 (0.74 to 2.54) 0.38 (0.03 to 4.63) P <=0.05 F7 90/960 (9.4%) 131/937 (14.0%) 34/259 (13.1%) 24/234 (10.3%) 2/14(14.3%) 1/21 (4.8%) 0.64 (0.48 to 0.85) 1.32 (0.63 to 2.76) 3.33 (0.26to 42.67) P <= 0.05 F7 90/941 (9.6%) 131/917 (14.3%) 34/256 (13.3%)24/231 (10.4%) 2/14 (14.3%) 1/21 (4.8%) 0.64 (0.48 to 0.85) 1.27 (0.73to 2.23) 3.73 (0.30 to 46.57) P <= 0.05 FABP1 55/599 (9.2%) 79/556(14.2%) 53/508 (10.4%) 68/513 (13.3%) 19/127 (15.0%) 11/126 (8.7%) 0.61(0.42 to 0.88) 0.76 (0.37 to 1.57) 1.84 (0.68 to 5.00) P <= 0.05 FABP155/410 (13.4%) 79/360 (21.9%) 53/352 (15.1%) 68/328 (20.7%) 19/91(20.9%) 11/84 (13.1%) 0.55 (0.38 to 0.80) 0.68 (0.32 to 1.44) 1.75 (0.62to 4.92) P <= 0.05 FABP1 55/402 (13.7%) 79/355 (22.3%) 53/346 (15.3%)68/324 (21.0%) 19/91 (20.9%) 11/82 (13.4%) 0.56 (0.38 to 0.83) 0.66(0.44 to 0.99) 1.73 (0.76 to 3.96) P <= 0.05 FCAR 115/1045 (11.0%)127/997 (12.7%) 11/160 (6.9%) 30/162 (18.5%) 1/8 (12.5%) 1/12 (8.3%)0.84 (0.64 to 1.10) 0.33 (0.16 to 0.69) 1.78 (0.09 to 33.90) P <= 0.05FN1 60/642 (9.3%) 94/616 (15.3%) 55/482 (11.4%) 50/463 (10.8%) 12/87(13.8%) 14/91 (15.4%) 0.56 (0.40 to 0.79) 1.08 (0.72 to 1.63) 0.92 (0.39to 2.14) P <= 0.05 GALC 99/593 (16.7%) 108/556 (19.4%) 22/209 (10.5%)43/182 (23.6%) 5/34 (14.7%) 2/15 (13.3%) 0.83 (0.62 to 1.12) 0.38 (0.18to 0.82) 1.12 (0.18 to 7.06) P <= 0.05 GAPD 88/540 (16.3%) 84/484(17.4%) 35/256 (13.7%) 57/232 (24.6%) 4/38 (10.5%) 10/35 (28.6%) 0.93(0.67 to 1.29) 0.49 (0.23 to 1.02) 0.29 (0.07 to 1.18) P <= 0.05 GAPD88/778 (11.3%) 84/737 (11.4%) 35/356 (9.8%) 57/351 (16.2%) 4/53 (7.5%)10/52 (19.2%) 0.98 (0.71 to 1.35) 0.57 (0.36 to 0.90) 0.31 (0.09 to1.07) P <= 0.05 GAPD 89/454 (19.6%) 164/534 (30.7%) 63/260 (24.2%)59/244 (24.2%) 10/26 (38.5%) 9/32 (28.1%) 0.54 (0.40 to 0.73) 0.99 (0.66to 1.49) 1.51 (0.50 to 4.55) P <= 0.05 GAPD 88/532 (16.5%) 84/479(17.5%) 35/251 (13.9%) 57/227 (25.1%) 4/38 (10.5%) 10/35 (28.6%) 0.92(0.66 to 1.28) 0.52 (0.32 to 0.83) 0.25 (0.07 to 0.93) P <= 0.05 GAPD89/429 (20.7%) 164/482 (34.0%) 63/238 (26.5%) 59/222 (26.6%) 10/23(43.5%) 9/32 (28.1%) 0.50 (0.37 to 0.67) 0.98 (0.65 to 1.49) 1.90 (0.62to 5.83) P <= 0.05 HLA-DPB1 59/606 (9.7%) 83/585 (14.2%) 51/514 (9.9%)69/505 (13.7%) 17/110 (15.5%) 6/98 (6.1%) 0.65 (0.46 to 0.93) 0.70 (0.34to 1.42) 2.80 (0.89 to 8.80) P <= 0.05 HLA-DPB1 59/429 (13.8%) 83/382(21.7%) 51/347 (14.7%) 69/313 (22.0%) 17/77 (22.1%) 6/71 (8.5%) 0.57(0.40 to 0.83) 0.61 (0.29 to 1.28) 3.07 (0.95 to 9.92) P <= 0.05HLA-DPB1 59/595 (9.9%) 83/577 (14.4%) 51/504 (10.1%) 69/492 (14.0%)17/109 (15.6%) 6/95 (6.3%) 0.65 (0.46 to 0.93) 0.68 (0.46 to 1.01) 2.88(1.08 to 7.67) P <= 0.05 HLA-DPB1 59/421 (14.0%) 83/379 (21.9%) 51/342(14.9%) 69/308 (22.4%) 17/76 (22.4%) 6/68 (8.8%) 0.56 (0.38 to 0.82)0.62 (0.41 to 0.93) 3.24 (1.18 to 8.91) P <= 0.005 HLA-DPB1 63/643(9.8%) 85/629 (13.5%) 49/502 (9.8%) 68/480 (14.2%) 15/88 (17.0%) 5/87(5.7%) 0.70 (0.49 to 0.98) 0.66 (0.32 to 1.33) 3.37 (1.00 to 11.32) P <=0.05 HLA-DPB1 63/453 (13.9%) 85/404 (21.0%) 49/334 (14.7%) 68/306(22.2%) 15/65 (23.1%) 5/62 (8.1%) 0.61 (0.42 to 0.87) 0.60 (0.29 to1.25) 3.42 (0.99 to 11.82) P <= 0.05 HLA-DPB1 63/633 (10.0%) 85/619(13.7%) 49/491 (10.0%) 68/469 (14.5%) 15/87 (17.2%) 5/84 (6.0%) 0.68(0.48 to 0.97) 0.66 (0.44 to 0.97) 3.52 (1.21 to 10.24) P <= 0.05HLA-DPB1 63/445 (14.2%) 85/401 (21.2%) 49/329 (14.9%) 68/301 (22.6%)15/64 (23.4%) 5/59 (8.5%) 0.59 (0.41 to 0.85) 0.62 (0.41 to 0.93) 3.77(1.25 to 11.36) P <= 0.005 HLA-DPB1 80/556 (14.4%) 108/492 (22.0%)39/265 (14.7%) 48/243 (19.8%) 8/32 (25.0%) 2/35 (5.7%) 0.60 (0.43 to0.82) 0.70 (0.34 to 1.43) 5.50 (0.98 to 30.84) P <= 0.05 HLA-DPB1 80/785(10.2%) 108/757 (14.3%) 39/385 (10.1%) 48/368 (13.0%) 8/42 (19.0%) 2/44(4.5%) 0.68 (0.50 to 0.93) 0.74 (0.47 to 1.17) 5.59 (1.10 to 28.50) P <=0.05 HLA-DPB1 80/546 (14.7%) 108/489 (22.1%) 39/262 (14.9%) 48/237(20.3%) 8/31 (25.8%) 2/33 (6.1%) 0.59 (0.43 to 0.82) 0.70 (0.43 to 1.13)6.70 (1.26 to 35.51) P <= 0.05 HLA-DPB1 74/747 (9.9%) 102/726 (14.0%)44/433 (10.2%) 52/407 (12.8%) 9/52 (17.3%) 3/59 (5.1%) 0.67 (0.49 to0.92) 0.77 (0.39 to 1.54) 3.91 (0.90 to 16.95) P <= 0.05 HLA-DPB1 74/523(14.1%) 102/468 (21.8%) 44/295 (14.9%) 52/256 (20.3%) 9/36 (25.0%) 3/45(6.7%) 0.59 (0.43 to 0.82) 0.69 (0.34 to 1.40) 4.66 (1.04 to 20.92) P <=0.05 HLA-DPB1 74/733 (10.1%) 102/717 (14.2%) 44/426 (10.3%) 52/395(13.2%) 9/51 (17.6%) 3/56 (5.4%) 0.68 (0.49 to 0.94) 0.74 (0.48 to 1.14)4.24 (1.07 to 16.85) P <= 0.05 HLA-DPB1 74/513 (14.4%) 102/465 (21.9%)44/292 (15.1%) 52/251 (20.7%) 9/35 (25.7%) 3/42 (7.1%) 0.59 (0.42 to0.83) 0.69 (0.44 to 1.08) 5.34 (1.29 to 22.12) P <= 0.05 HLA-DQB1 92/840(11.0%) 111/840 (13.2%) 28/361 (7.8%) 44/314 (14.0%) 7/35 (20.0%) 3/40(7.5%) 0.81 (0.60 to 1.08) 0.52 (0.25 to 1.05) 3.08 (0.67 to 14.16) P <=0.05 HLA-DQB1 92/583 (15.8%) 111/545 (20.4%) 28/247 (11.3%) 44/201(21.9%) 7/24 (29.2%) 3/25 (12.0%) 0.73 (0.54 to 0.99) 0.46 (0.22 to0.95) 3.02 (0.62 to 14.69) P <= 0.05 HLA-DQB1 92/826 (11.1%) 111/823(13.5%) 28/353 (7.9%) 44/308 (14.3%) 7/35 (20.9%) 3/40 (7.5%) 0.81 (0.60to 1.09) 0.51 (0.31 to 0.85) 2.83 (0.66 to 12.08) P <= 0.05 HLA-DQB192/572 (16.1%) 111/536 (20.7%) 28/244 (11.5%) 44/200 (22.0%) 7/24(29.2%) 3/25 (12.0%) 0.74 (0.55 to 1.02) 0.45 (0.27 to 0.76) 2.93 (0.64to 13.37) P <= 0.05 HRC 59/253 (23.3%) 65/247 (26.3%) 65/361 (18.0%)124/402 (30.8%) 35/127 (27.6%) 42/164 (25.6%) 0.84 (0.56 to 1.26) 0.49(0.35 to 0.69) 1.08 (0.64 to 1.82) P <= 0.05 HRC 59/234 (25.2%) 65/221(29.4%) 65/338 (19.2%) 124/368 (33.7%) 35/118 (29.7%) 42/151 (27.8%)0.80 (0.53 to 1.21) 0.46 (0.33 to 0.66) 1.08 (0.63 to 1.83) P <= 0.05IL1A 77/370 (20.8%) 134/400 (33.5%) 74/306 (24.2%) 86/351 (4.5%) 11/60(18.3%) 11/61 (18.0%) 0.52 (0.38 to 0.73) 0.95 (0.66 to 1.36) 0.95 (0.38to 2.40) P <= 0.05 IL1RN 66/642 (10.3%) 81/623 (13.0%) 43/496 (8.7%)66/461 (14.3%) 17/95 (17.9%) 11/101 (10.9%) 0.77 (0.54 to 1.08) 0.57(0.28 to 1.16) 1.78 (0.65 to 4.88) P <= 0.05 IL1RN 66/453 (14.6%) 81/404(20.0%) 43/335 (12.8%) 66/290 (22.8%) 17/63 (27.0%) 11/70 (15.7%) 0.68(0.48 to 0.97) 0.50 (0.24 to 1.05) 1.98 (0.70 to 5.65) P <= 0.05 IL1RN66/444 (14.9%) 81/396 (20.5%) 43/332 (13.0%) 66/289 (22.8%) 17/62(27.4%) 11/69 (15.9%) 0.65 (0.45 to 0.94) 0.53 (0.35 to 0.82) 1.96 (0.82to 4.65) P <= 0.05 IL9 111/911 (12.2%) 116/919 (12.6%) 15/290 (5.2%)39/253 (15.4%) 1/28 (3.6%) 3/21 (14.3%) 0.96 (0.73 to 1.27) 0.30 (0.14to 0.66) 0.22 (0.02 to 2.42) P <= 0.005 IL9 111/644 (17.2%) 116/591(19.6%) 15/187 (8.0%) 39/169 (23.1%) 1/19 (5.3%) 3/11 (27.3%) 0.85 (0.64to 1.14) 0.29 (0.13 to 0.65) 0.15 (0.01 to 1.74) P <= 0.005 IL9 111/896(12.4%) 116/901 (12.9%) 15/283 (5.3%) 39/247 (15.8%) 1/28 (3.6%) 3/21(14.3%) 0.95 (0.72 to 1.26) 0.30 (0.16 to 0.56) 0.21 (0.02 to 2.18) P <=0.005 IL9 111/633 (17.5%) 116/583 (19.9%) 15/184 (8.2%) 39/166 (23.5%)1/19 (5.3%) 3/11 (27.3%) 0.85 (0.63 to 1.14) 0.30 (0.16 to 0.57) 0.16(0.01 to 1.77) P <= 0.005 ITGA4 120/1204 (10.0%) 155/1162 (13.3%) 5/21(23.8%) 2/30 (6.7%) 0/0 (0.0%) 0/0 (0.0%) 0.72 (0.56 to 0.93) 4.38 (0.72to 26.56) P <= 0.05 ITGA4 120/1183 (10.1%) 155/1138 (13.6%) 5/20 (25.0%)2/30 (6.7%) 0/0 (0.0%) 0/0 (0.0%) 0.71 (0.55 to 0.92) 5.66 (0.96 to33.29) P <= 0.05 ITGA4 120/817 (14.7%) 155/740 (20.9%) 5/16 (31.3%) 2/18(11.1%) 0/0 (0.0%) 0/0 (0.0%) 0.65 (0.50 to 0.85) 4.64 (0.74 to 29.19) P<= 0.05 KDR 87/985 (8.8%) 130/961 (13.5%) 39/235 (16.6%) 25/215 (11.6%)1/15 (6.7%) 2/18 (11.1%) 0.62 (0.46 to 0.83) 1.51 (0.73 to 3.12) 0.57(0.04 to 7.33) P <= 0.05 KDR 87/675 (12.9%) 130/620 (21.0%) 39/168(23.2%) 25/141 (17.7%) 1/10 (10.0%) 2/10 (20.0%) 0.56 (0.41 to 0.75)1.40 (0.66 to 2.98) 0.44 (0.03 to 6.17) P <= 0.05 KDR 87/971 (9.0%)130/946 (13.7%) 39/227 (17.2%) 25/206 (1 2.1%) 1/15 (6.7%) 2/18 (11.1%)0.60 (0.45 to 0.81) 1.63 (0.94 to 2.82) 0.67 (0.05 to 8.25) P <= 0.05KDR 87/666 (13.1%) 130/614 (21.2%) 39/163 (23.9%) 25/136 (18.4%) 1/10(10.0%) 2/10 (20.0%) 0.54 (0.40 to 0.73) 1.59 (0.90 to 2.82) 0.52 (0.04to 6.89) P <= 0.005 KDR 87/983 (8.9%) 129/958 (13.5%) 39/234 (16.7%)25/214 (11.7%) 1/16 (6.3%) 2/18 (11.1%) 0.62 (0.47 to 0.83) 1.51 (0.73to 3.12) 0.53 (0.04 to 6.82) P <= 0.05 KDR 87/674 (12.9%) 129/617(20.9%) 39/167 (23.4%) 25/140 (17.9%) 1/11 (9.1%) 2/10 (20.0%) 0.56(0.42 to 0.75) 1.40 (0.66 to 2.98) 0.40 (0.03 to 5.51) P <= 0.05 KDR87/969 (9.0%) 129/943 (13.7%) 39/226 (17.3%) 25/206 (12.1%) 1/16 (6.3%)2/18 (11.1%) 0.61 (0.45 to 0.81) 1.64 (0.95 to 2.83) 0.62 (0.05 to 7.67)P <= 0.05 KDR 87/665 (13.1%) 129/611 (21.1%) 39/162 (24.1%) 25/136(18.4%) 1/11 (9.1%) 2/10 (20.0%) 0.54 (0.40 to 0.74) 1.60 (0.90 to 2.84)0.46 (0.03 to 6.09) P <= 0.005 KLK14 60/560 (10.7%) 61/560 (10.9%)57/556 (10.3%) 68/511 (13.3%) 9/114 (7.9%) 27/115 (23.5%) 0.98 (0.67 to1.43) 0.74 (0.35 to 1.58) 0.28 (0.10 to 0.79) P <= 0.05 KLK14 60/374(16.0%) 61/353 (17.3%) 57/404 (1 4.1%) 68/334 (20.4%) 9/70 (12.9%) 27/80(33.8%) 0.91 (0.62 to 1.35) 0.64 (0.29 to 1.40) 0.29 (0.10 to 0.85) P <=0.05 KLK14 60/548 (10.9%) 61/548 (11.1%) 57/547 (10.4%) 68/501 (13.6%)9/113 (8.0%) 27/113 (23.9%) 0.96 (0.66 to 1.41) 0.75 (0.51 to 1.09) 0.28(0.12 to 0.63) P <= 0.05 KLK14 60/365 (16.4%) 61/349 (17.5%) 57/399(14.3%) 68/328 (20.7%) 9/70 (12.9%) 27/79 (34.2%) 0.92 (0.62 to 1.37)0.65 (0.44 to 0.97) 0.28 (0.12 to 0.65) P <= 0.05 LPA 88/627 (14.0%)128/565 (22.7%) 29/188 (15.4%) 25/178 (14.0%) 7/17 (41.2%) 3/11 (27.3%)0.56 (0.41 to 0.76) 1.13 (0.63 to 2.03) 2.42 (0.46 to 12.85) P <= 0.05LRP3 133/552 (24.1%) 171/621 (27.5%) 25/172 (14.5%) 59/176 (33.5%) 3/11(27.3%) 3/15 (20.0%) 0.82 (0.63 to 1.07) 0.33 (0.20 to 0.57) 1.46 (0.23to 9.19) P <= 0.05 LRP3 133/509 (26.1%) 171/563 (30.4%) 25/164 (15.2%)59/163 (36.2%) 3/11 (27.3%) 3/13 (23.1%) 0.80 (0.61 to 1.04) 0.31 (0.18to 0.54) 1.21 (0.19 to 7.76) P <= 0.05 MYH7 118/1200 (9.8%) 154/1144(13.5%) 9/31 (29.0%) 2/47 (4.3%) 0/0 (0.0%) 0/0 (0.0%) 0.70 (0.54 to0.90) 9.19 (1.73 to 48.90) P <= 0.005 MYH7 118/829 (14.2%) 154/739(20.8%) 9/22 (40.9%) 2/28 (7.1%) 0/0 (0.0%) 0/0 (0.0%) 0.63 (0.48 to0.82) 9.00 (1.60 to 50.73) P <= 0.005 MYH7 118/1178 (10.0%) 154/1122(13.7%) 9/31 (29.0%) 2/45 (4.4%) 0/0 (0.0%) 0/0 (0.0%) 0.70 (0.54 to0.90) 8.60 (1.70 to 43.64) P <= 0.005 MYH7 118/815 (14.5%) 154/729(21.1%) 9/22 (40.9%) 2/27 (7.4%) 0/0 (0.0%) 0/0 (0.0%) 0.63 (0.48 to0.83) 8.16 (1.51 to 44.20) P <= 0.005 NOS3 53/539 (9.8%) 66/528 (12.5%)64/527 (12.1%) 67/526 (12.7%) 10/169 (5.9%) 23/140 (16.4%) 0.76 (0.52 to1.12) 0.95 (0.45 to 2.00) 0.32 (0.12 to 0.88) P <= 0.05 NOS3 53/368(14.4%) 66/335 (19.7%) 64/366 (17.5%) 67/344 (19.5%) 10/119 (8.4%) 23/91(25.3%) 0.69 (0.46 to 1.02) 0.88 (0.40 to 1.90) 0.27 (0.09 to 0.78) P <=0.05 NOS3 53/529 (10.0%) 66/515 (12.8%) 64/520 (12.3%) 67/521 (12.9%)10/164 (6.1%) 23/134 (17.2%) 0.75 (0.51 to 1.10) 0.95 (0.66 to 1.38)0.32 (0.15 to 0.70) P <= 0.05 NOS3 53/359 (14.8%) 66/327 (20.2%) 64/363(17.6%) 67/342 (19.6%) 10/117 (8.5%) 23/90 (25.6%) 0.66 (0.44 to 0.99)0.90 (0.61 to 1.32) 0.29 (0.13 to 0.64) P <= 0.05 NPC1 53/307 (17.3%)45/290 (15.5%) 51/386 (13.2%) 81/376 (21.5%) 22/150 (14.7%) 31/98(31.6%) 1.14 (0.74 to 1.75) 0.55 (0.24 to 1.30) 0.37 (0.14 to 0.99) P <=0.05 NPC1 53/304 (17.4%) 45/287 (15.7%) 51/378 (13.5%) 81/370 (21.9%)22/147 (15.0%) 31/96 (32.3%) 1.09 (0.70 to 1.69) 0.58 (0.39 to 0.86)0.37 (0.20 to 0.70) P <= 0.05 NPC1 44/240 (18.3%) 36/217 (16.6%) 56/408(13.7%) 81/387 (20.9%) 27/196 (13.8%) 40/160 (25.0%) 1.13 (0.70 to 1.83)0.60 (0.24 to 1.52) 0.48 (0.17 to 1.31) P <= 0.05 PLAB 84/706 (11.9%)82/675 (12.1%) 38/455 (8.4%) 68/443 (15.3%) 5/72 (6.9%) 8/75 (10.7%)0.98 (0.71 to 1.35) 0.50 (0.25 to 1.02) 0.63 (0.17 to 2.28) P <= 0.05PLAB 84/691 (12.2%) 82/660 (12.4%) 38/448 (8.5%) 68/437 (15.6%) 5/72(6.9%) 8/73 (11.0%) 0.98 (0.71 to 1.36) 0.49 (0.32 to 0.75) 0.62 (0.19to 2.02) P <= 0.05 PLAB 84/481 (17.5%) 82/426 (19.2%) 38/302 (12.6%)68/284 (23.9%) 5/56 (8.9%) 8/50 (16.0%) 0.90 (0.64 to 1.26) 0.44 (0.28to 0.69) 0.57 (0.17 to 1.89) P <= 0.05 PPOX 116/1036 (11.2%) 128/1019(12.6%) 10/169 (5.9%) 25/143 (17.5%) 1/6 (16.7%) 1/5 (20.0%) 0.88 (0.67to 1.15) 0.30 (0.12 to 0.73) 0.80 (0.04 to 17.80) P <= 0.05 PPOX 116/721(16.1%) 128/667 (19.2%) 10/113 (8.8%) 25/85 (29.4%) 1/3 (33.3%) 1/2(50.0%) 0.81 (0.61 to 1.06) 0.23 (0.09 to 0.59) 0.50 (0.01 to 20.18) P<= 0.05 PPOX 116/1020 (11.4%) 128/999 (12.8%) 10/164 (6.1%) 25/139(18.0%) 1/6 (16.7%) 1/5 (20.0%) 0.87 (0.66 to 1.14) 0.29 (0.13 to 0.63)1.22 (0.06 to 27.04) P <= 0.05 PPOX 116/711 (16.3%) 128/658 (19.5%)10/110 (9.1%) 25/83 (30.1%) 1/3 (33.3%) 1/2 (50.0%) 0.80 (0.60 to 1.06)0.26 (0.11 to 0.58) 0.85 (0.02 to 35.51) P <= 0.05 SELL 99/930 (10.6%)105/883 (11.9%) 23/273 (8.4%) 52/291 (17.9%) 4/31 (12.9%) 1/19 (5.3%)0.88 (0.66 to 1.18) 0.42 (0.20 to 0.87) 2.67 (0.26 to 27.29) P <= 0.05SELL 99/915 (10.8%) 105/870 (12.1%) 23/269 (8.6%) 52/280 (18.6%) 4/28(14.3%) 1/19 (5.3%) 0.88 (0.65 to 1.18) 0.42 (0.25 to 0.71) 2.47 (0.25to 24.40) P <= 0.05 SELL 100/930 (10.8%) 104/882 (11.8%) 23/276 (8.3%)52/294 (17.7%) 4/30 (13.3%) 1/19 (5.3%) 0.90 (0.67 to 1.21) 0.42 (0.20to 0.87) 2.77 (0.27 to 28.37) P <= 0.05 SELL 100/915 (10.9%) 104/869(12.0%) 23/272 (8.5%) 52/283 (18.4%) 4/27 (14.8%) 1/19 (5.3%) 0.90 (0.67to 1.20) 0.42 (0.25 to 0.71) 2.49 (0.25 to 24.61) P <= 0.05 SERPINA180/489 (16.4%) 86/427 (20.1%) 29/199 (14.6%) 32/181 (17.7%) 10/119(8.4%) 29/117 (24.8%) 0.78 (0.55 to 1.09) 0.79 (0.36 to 1.77) 0.28 (0.11to 0.73) P <= 0.05 SERPINA1 80/481 (16.6%) 86/418 (20.6%) 29/198 (14.6%)32/180 (17.8%) 10/116 (8.6%) 29/117 (24.8%) 0.78 (0.55 to 1.10) 0.81(0.46 to 1.42) 0.27 (0.12 to 0.58) P <= 0.05 SERPINA5 60/560 (10.7%)65/553 (11.8%) 44/526 (8.4%) 81/527 (15.4%) 23/142 (16.2%) 12/113(10.6%) 0.90 (0.62 to 1.31) 0.50 (0.24 to 1.06) 1.63 (0.61 to 4.35) P <=0.05 SERPINA5 60/407 (14.7%) 65/364 (17.9%) 44/347 (12.7%) 81/337(24.0%) 23/95 (24.2%) 12/69 (17.4%) 0.80 (0.54 to 1.17) 0.46 (0.21 to1.00) 1.52 (0.55 to 4.22) P <= 0.05 SERPINA5 60/554 (10.8%) 65/545(11.9%) 44/515 (8.5%) 81/514 (15.8%) 23/138 (16.7%) 12/110 (10.9%) 0.91(0.62 to 1.32) 0.49 (0.33 to 0.73) 1.55 (0.73 to 3.30) P <= 0.05SERPINA5 60/402 (14.9%) 65/359 (18.1%) 44/339 (13.0%) 81/333 (24.3%)23/94 (24.5%) 12/67 (17.9%) 0.80 (0.54 to 1.18) 0.46 (0.31 to 0.70) 1.46(0.66 to 3.26) P <= 0.05 SERPINB6 74/609 (12.2%) 66/574 (11.5%) 45/505(8.9%) 70/504 (13.9%) 8/118 (6.8%) 21/111 (18.9%) 1.06 (0.75 to 1.52)0.61 (0.29 to 1.26) 0.31 (0.11 to 0.90) P <= 0.05 SERPINB6 74/433(17.1%) 66/360 (18.3%) 45/334 (13.5%) 70/333 (21.0%) 8/84 (9.5%) 21/74(28.4%) 0.92 (0.64 to 1.32) 0.59 (0.27 to 1.25) 0.27 (0.09 to 0.79) P <=0.05 SERPINB6 74/598 (12.4%) 66/564 (11.7%) 45/498 (9.0%) 70/493 (14.2%)8/114 (7.0%) 21/108 (19.4%) 1.05 (0.74 to 1.51) 0.61 (0.41 to 0.91) 0.30(0.13 to 0.71) P <= 0.05 SERPINB6 74/425 (17.4%) 66/356 (18.5%) 45/328(13.7%) 70/327 (21.4%) 8/84 (9.5%) 21/73 (28.8%) 0.92 (0.63 to 1.34)0.60 (0.40 to 0.91) 0.24 (0.10 to 0.58) P <= 0.05 SERPINI2 54/483(11.2%) 51/470 (10.9%) 51/565 (9.0%) 90/541 (16.6%) 22/187 (11.8%)17/179 (9.5%) 1.03 (0.69 to 1.55) 0.50 (0.22 to 1.10) 1.27 (0.48 to3.36) P <= 0.05 SERPINI2 54/332 (16.3%) 51/299 (17.1%) 51/382 (13.4%)90/354 (25.4%) 22/139 (15.8%) 17/116 (14.7%) 0.94 (0.62 to 1.44) 0.54(0.20 to 1.03) 1.10 (0.40 to 1.87) P <= 0.05 SERPINI2 54/477 (11.3%)51/460 (11.1%) 51/554 (9.2%) 90/531 (16.9%) 22/182 (12.1%) 17/175 (9.7%)1.02 (0.68 to 1.54) 0.50 (0.35 to 0.73) 1.24 (0.63 to 2.43) P <= 0.05SERPINI2 54/326 (16.6%) 51/294 (17.3%) 51/377 (13.5%) 90/531 (25.6%)22/136 (16.2%) 17/113 (15.0%) 0.95 (0.62 to 1.46) 0.46 (0.31 to 0.68)1.06 (0.53 to 2.12) P <= 0.05 TNF 96/590 (16.3%) 103/541 (19.0%) 28/227(12.3%) 50/220 (22.7%) 3/35 (8.6%) 5/10 (50.0%) 0.83 (0.61 to 1.12) 0.48(0.23 to 0.99) 0.09 (0.02 to 0.56) P <= 0.05 TNF 96/581 (16.5%) 103/532(19.4%) 28/223 (12.6%) 50/218 (22.9%) 3/34 (8.8%) 5/10 (50.0%) 0.83(0.60 to 1.13) 0.48 (0.29 to 0.81) 0.11 (0.02 to 0.61) P <= 0.05 VTN39/340 (11.5%) 32/361 (8.9%) 64/629 (10.2%) 93/567 (16.4%) 24/266 (9.0%)33/268 (12.3%) 1.33 (0.81 to 2.18) 0.58 (0.23 to 1.46) 0.71 (0.25 to1.98) P <= 0.05 VTN 39/240 (16.3%) 32/220 (14.5%) 64/436 (14.7%) 93/376(24.7%) 24/177 (13.6%) 33/176 (18.8%) 1.14 (0.69 to 1.89) 0.52 (0.20 to1.37) 0.68 (0.24 to 1.96) P <= 0.05 VTN 39/334 (11.7%) 32/351 (9.1%)64/620 (10.3%) 93/559 (16.6%) 24/259 (9.3%) 33/262 (12.6%) 1.31 (0.80 to2.15) 0.56 (0.40 to 0.80) 0.73 (0.41 to 1.28) P <= 0.05 VTN 39/236(16.5%) 32/216 (14.8%) 64/432 (14.8%) 93/371 (25.1%) 24/171 (14.0%)33/174 (19.0%) 1.19 (0.71 to 2.01) 0.51 (0.36 to 0.73) 0.70 (0.39 to1.25) P <= 0.05 *For the CARE prospective study: results of the OverallScore Test (chi-square test) tor the logistic regression model in whichthe phenotype (case definition) is a function of the SNP genotype,treatment group, and the interaction between SNP genotype and treatmentgroup. For case/control studies: results of the Overall Score Test(chi-square test) for the conditional logistic regression model in whichthe phenotype (case definition) is a function of the SNP genotype,treatment group, and the interaction between SNP genotype and treatmentgroup and cases and controls have been matched on age and smokingstatus. **For the CARE prospective study: results of the chi-square testof the interaction between SNP genotype and treatment group (based onthe logistic regression model). For the case/control studies: results ofthe chi-square test of the interaction between SNP genotype andtreatment group (based on the conditional logistic regression model).***All Possible Controls include all controls with genotype data.Cleaner controls include controls with genotype data but with no otherCVD-related events during the trial. For case definition, “F MI/SD/NFMI” = Fatal MI/Sudden Death/Definite Nonfatal MI For case definition,“F&NF MI” = Fatal & Notfatal MI For stratum, “WM” = White Males Forstudy, “W” = WOSCOPS

TABLE 14 Statistically Significant Associations Between SNP ControlOverall* Chi- Genotypes and Two CVD Case Definitions: Group Square TestFatal MI/Sudden Death/ Definite Non-fatal MI and Fatal/Non-fatal MIDefin- Stra- Stati- p- Public Marker Study Study Design Case Definitionition tum stic value ABCA1 hCV2741083 CARE Prospective F MI/SD/NF MI AllPossible WM 6.3 0.0428 ABCA1 hCV2741083 CARE Prospective F MI/SD/NF MICleaner WM 7.75 0.0207 ABCA1 hCV2741083 CARE Case/Control F MI/SD/NF MIAll Possible WM 7.81 0.0201 ABCA1 hCV2741083 W Case/Control F MI/SD/NFMI All Possible WM 7.56 0.0229 ABCA1 hCV2741083 CARE Case/Control FMI/SD/NF MI Cleaner WM 7.97 0.0186 ABCA1 hCV2741083 W Case/Control FMI/SD/NF MI Cleaner WM 6.4 0.0408 ABO hCV25610774 CARE Case/Control FMI/SD/NF MI Cleaner WM 6.53 0.0382 ABO hCV25610819 CARE Case/Control FMI/SD/NF MI All Possible WM 6.21 0.0449 ABO hCV25610819 CARECase/Control F MI/SD/NF MI Cleaner WM 7.34 0.0255 ABO hCV8784787 CARECase/Control F MI/SD/NF MI Cleaner WM 6.84 0.0327 ADAMTS1 hCV529706 CARECase/Control F MI/SD/NF MI All Possible WM 6.5 0.0388 ADAMTS1 hCV529706CARE Case/Control F MI/SD/NF MI Cleaner WM 6.41 0.0405 ADAMTS1 hCV529710CARE Prospective F MI/SD/NF MI Cleaner WM 5.99 0.0499 ADAMTS1 hCV529710CARE Case/Control F MI/SD/NF MI All Possible WM 6.95 0.031 ADAMTS1hCV529710 CARE Case/Control F MI/SD/NF MI Cleaner WM 7.01 0.0301 APOBhCV25990803 CARE Case/Control F MI/SD/NF MI All Possible WM 10.07 0.0015APOB hCV3216558 CARE Case/Control F MI/SD/NF MI Cleaner WM 6.15 0.0462APOB hCV7615376 CARE Case/Control F MI/SD/NF MI Cleaner WM 6.19 0.0452ASAH1 hCV2442143 CARE Prospective F MI/SD/NF MI Cleaner WM 7.17 0.0278ASAH1 hCV2442143 CARE Case/Control F MI/SD/NF MI All Possible WM 7.980.0185 ASAH1 hCV2442143 CARE Case/Control F MI/SD/NF MI Cleaner WM 10.340.0057 ATF6 hCV25631989 CARE Prospective F MI/SD/NF MI Cleaner WM 7.080.0291 ATF6 hCV25631989 CARE Case/Control F MI/SD/NF MI Cleaner WM 7.710.0212 BAIAP3 hCV2503034 CARE Prospective F MI/SD/NF MI All Possible WM8.74 0.0126 BAIAP3 hCV2503034 CARE Prospective F MI/SD/NF MI Cleaner WM10.16 0.0062 BAIAP3 hCV2503034 CARE Case/Control F MI/SD/NF MI AllPossible WM 7.89 0.0193 BAIAP3 hCV2503034 CARE Case/Control F MI/SD/NFMI Cleaner WM 8.23 0.0164 BAT2 hCV7514722 CARE Prospective F MI/SD/NF MIAll Possible WM 6.4 0.0409 BAT2 hCV7514722 CARE Prospective F MI/SD/NFMI Cleaner WM 7.47 0.0239 BAT2 hCV7514722 CARE Case/Control F MI/SD/NFMI All Possible WM 6.34 0.042 BAT2 hCV7514722 CARE Case/Control FMI/SD/NF MI Cleaner WM 7.11 0.0286 BDKRB2 hCV25933600 CARE Prospective FMI/SD/NF MI All Possible WM 6.04 0.0487 BDKRB2 hCV25933600 CAREProspective F MI/SD/NF MI Cleaner WM 6.29 0.043 CAPN2 hCV781558 WCase/Control F MI/SD/NF MI All Possible WM 7.68 0.0215 CAPN2 hCV781558 WCase/Control F MI/SD/NF MI Cleaner WM 9.12 0.0104 CASP1 hCV16276495 CAREProspective F MI/SD/NF MI All Possible WM 12.26 0.0005 CASP1 hCV16276495CARE Prospective F MI/SD/NF MI Cleaner WM 10.7 0.0011 CASP1 hCV16276495CARE Case/Control F MI/SD/NF MI All Possible WM 9.14 0.0025 CASP1hCV16276495 CARE Case/Control F MI/SD/NF MI Cleaner WM 8.34 0.0039 CCKBRhCV9604851 CARE Prospective F MI/SD/NF MI All Possible WM 13.75 0.001CCKBR hCV9604851 CARE Prospective F MI/SD/NF MI Cleaner WM 12.61 0.0018CCKBR hCV9604851 CARE Case/Control F MI/SD/NF MI All Possible WM 11.840.0027 CCKBR hCV9604851 CARE Case/Control F MI/SD/NF MI Cleaner WM 9.260.0098 CCL22 hCV3268420 CARE Prospective F MI/SD/NF MI All Possible WM11.27 0.0036 CCL22 hCV3268420 CARE Case/Control F MI/SD/NF MI AllPossible WM 12.98 0.0015 CCRL2 hCV25637308 CARE Prospective F MI/SD/NFMI All Possible WM 12.07 0.0024 CCRL2 hCV25637308 CARE Prospective FMI/SD/NF MI Cleaner WM 8.98 0.0112 CCRL2 hCV25637308 CARE Case/Control FMI/SD/NF MI All Possible WM 13.52 0.0012 CCRL2 hCV25637308 CARECase/Control F MI/SD/NF MI Cleaner WM 7.02 0.0299 CCRL2 hCV25637309 CAREProspective F MI/SD/NF MI Cleaner WM 6.17 0.0456 COL2A1 hCV25606528 CARECase/Control F MI/SD/NF MI All Possible WM 6.1 0.0474 CPT1A hCV15851335CARE Prospective F MI/SD/NF MI All Possible WM 9.05 0.0108 CR1hCV25598589 CARE Case/Control F MI/SD/NF MI All Possible WM 5.25 0.022CR1 hCV25598589 CARE Case/Control F MI/SD/NF MI Cleaner WM 6.01 0.0142CX3CR1 hCV7900503 CARE Prospective F MI/SD/NF MI All Possible WM 7.890.0193 CX3CR1 hCV7900503 CARE Prospective F MI/SD/NF MI Cleaner WM 8.190.0167 CX3CR1 hCV7900503 CARE Case/Control F MI/SD/NF MI All Possible WM7.39 0.0249 CX3CR1 hCV7900503 CARE Case/Control F MI/SD/NF MI Cleaner WM6.9 0.0317 DBH hCV12020339 CARE Case/Control F MI/SD/NF MI Cleaner WM9.48 0.0087 F7 hCV783184 W Case/Control F MI/SD/NF MI All Possible WM6.41 0.0406 F7 hCV783184 W Case/Control F MI/SD/NF MI Cleaner WM 6.680.0354 GBA hCV2276802 CARE Prospective F MI/SD/NF MI Cleaner WM 7.050.0079 HLA-A hCV11689916 CARE Prospective F MI/SD/NF MI All Possible WM6.49 0.039 HLA-A hCV11689916 CARE Case/Control F MI/SD/NF MI AllPossible WM 6.08 0.0478 HLA-DPB1 hCV11916894 CARE Prospective F MI/SD/NFMI All Possible WM 6.68 0.0354 HLA-DPB1 hCV11916894 CARE Prospective FMI/SD/NF MI Cleaner WM 10.56 0.0051 HLA-DPB1 hCV11916894 CARECase/Control F MI/SD/NF MI Cleaner WM 8.93 0.0115 HLA-DPB1 hCV25651174CARE Prospective F MI/SD/NF MI Cleaner WM 7.46 0.024 HLA-DPB1hCV25651174 CARE Case/Control F MI/SD/NF MI Cleaner WM 7.05 0.0295HLA-DPB1 hCV8851065 CARE Prospective F MI/SD/NF MI Cleaner WM 7.180.0276 HSPG2 hCV1603656 W Case/Control F MI/SD/NF MI All Possible WM 6.40.0408 HSPG2 hCV1603656 W Case/Control F MI/SD/NF MI Cleaner WM 7.430.0243 IL1A hCV9546471 W Case/Control F MI/SD/NF MI All Possible WM 7.560.0228 IL1A hCV9546471 W Case/Control F MI/SD/NF MI Cleaner WM 7.870.0195 IL1B hCV9546517 CARE Case/Control F MI/SD/NF MI Cleaner WM 6.10.0474 IL1RL1 hCV25607108 CARE Prospective F MI/SD/NF MI All Possible WM9.45 0.0089 IL1RL1 hCV25607108 CARE Case/Control F MI/SD/NF MI AllPossible WM 10.51 0.0052 IL1RL1 hCV25607108 CARE Case/Control F MI/SD/NFMI Cleaner WM 7.32 0.0257 IL4R hCV2769554 CARE Prospective F MI/SD/NF MIAll Possible WM 8.2 0.0165 IL4R hCV2769554 CARE Prospective F MI/SD/NFMI Cleaner WM 7.04 0.0296 IL4R hCV2769554 CARE Case/Control F MI/SD/NFMI All Possible WM 10.46 0.0053 IL4R hCV2769554 CARE Case/Control FMI/SD/NF MI Cleaner WM 8.54 0.014 ITGA9 hCV25644901 CARE Prospective FMI/SD/NF MI Cleaner WM 11.24 0.0008 KIAA0329 hCV25751017 CAREProspective F MI/SD/NF MI All Possible WM 6.98 0.0082 KIAA0329hCV25751017 CARE Prospective F MI/SD/NF MI Cleaner WM 6.8 0.0091 KLK14hCV16044337 CARE Prospective F MI/SD/NF MI All Possible WM 12.02 0.0025KLK14 hCV16044337 CARE Prospective F MI/SD/NF MI Cleaner WM 10.52 0.0052KLK14 hCV16044337 CARE Case/Control F MI/SD/NF MI All Possible WM 130.0015 KLK14 hCV16044337 CARE Case/Control F MI/SD/NF MI Cleaner WM12.07 0.0024 KLKB1 hCV22272267 CARE Prospective F MI/SD/NF MI AllPossible WM 6.55 0.0379 KLKB1 hCV22272267 CARE Case/Control F MI/SD/NFMI All Possible WM 7.61 0.0223 KLKB1 hCV22272267 CARE Case/Control FMI/SD/NF MI Cleaner WM 6.3 0.0428 LAPTM5 hCV25632652 CARE Prospective FMI/SD/NF MI All Possible WM 7.22 0.0271 LAPTM5 hCV25632652 CARECase/Control F MI/SD/NF MI All Possible WM 7.4 0.0247 LRP2 hCV16165996CARE Prospective F MI/SD/NF MI Cleaner WM 6.37 0.0414 LRP2 hCV16165996 WCase/Control F MI/SD/NF MI All Possible WM 7.7 0.0213 LRP2 hCV16165996CARE Case/Control F MI/SD/NF MI Cleaner WM 6.12 0.047 LRP2 hCV16165996 WCase/Control F MI/SD/NF MI Cleaner WM 9.52 0.0086 LTA hCV7514870 CAREProspective F MI/SD/NF MI All Possible WM 6.37 0.0415 LTA hCV7514870CARE Prospective F MI/SD/NF MI Cleaner WM 7.34 0.0255 LTA hCV7514870CARE Case/Control F MI/SD/NF MI All Possible WM 7.11 0.0286 LTAhCV7514870 CARE Case/Control F MI/SD/NF MI Cleaner WM 6.17 0.0458 MARK3hCV25926771 CARE Prospective F MI/SD/NF MI All Possible WM 3.98 0.0461MARK3 hCV25926771 CARE Prospective F MI/SD/NF MI Cleaner WM 3.93 0.0474MC1R hCV11951095 CARE Prospective F MI/SD/NF MI Cleaner WM 6.79 0.0092MMP7 hCV3210838 CARE Prospective F MI/SD/NF MI All Possible WM 8.20.0166 MMP7 hCV3210838 CARE Prospective F MI/SD/NF MI Cleaner WM 7.010.0301 MMP7 hCV3210838 CARE Case/Control F MI/SD/NF MI All Possible WM7.4 0.0248 MMP7 hCV3210838 CARE Case/Control F MI/SD/NF MI Cleaner WM7.66 0.0217 MMP8 hCV11484594 CARE Prospective F MI/SD/NF MI Cleaner WM6.33 0.0422 MTR hCV16172188 CARE Prospective F MI/SD/NF MI All PossibleWM 4.82 0.0282 MTR hCV16172188 CARE Prospective F MI/SD/NF MI Cleaner WM4.17 0.0413 NDUFS2 hCV25653285 CARE Prospective F MI/SD/NF MI AllPossible WM 4.65 0.0311 NDUFS2 hCV25653285 CARE Case/Control F MI/SD/NFMI All Possible WM 6.66 0.0099 NDUFS2 hCV25653285 CARE Case/Control FMI/SD/NF MI Cleaner WM 5.09 0.024 NOS2A hCV11889257 CARE Prospective FMI/SD/NF MI All Possible WM 6.53 0.0383 NOS2A hCV11889257 CAREProspective F MI/SD/NF MI Cleaner WM 6.93 0.0313 NOS2A hCV11889257 CARECase/Control F MI/SD/NF MI All Possible WM 7.19 0.0274 NOS2A hCV11889257CARE Case/Control F MI/SD/NF MI Cleaner WM 6.82 0.0331 NPC1 hCV25472673CARE Prospective F MI/SD/NF MI All Possible WM 7.63 0.022 NPC1hCV25472673 CARE Prospective F MI/SD/NF MI Cleaner WM 13.16 0.0014 NPC1hCV25472673 CARE Case/Control F MI/SD/NF MI All Possible WM 6.45 0.0397NPC1 hCV25472673 CARE Case/Control F MI/SD/NF MI Cleaner WM 10.66 0.0048PDGFRA hCV22271841 CARE Prospective F MI/SD/NF MI All Possible WM 15.640.0004 PDGFRA hCV22271841 CARE Prospective F MI/SD/NF MI Cleaner WM13.98 0.0009 PDGFRA hCV22271841 CARE Case/Control F MI/SD/NF MI AllPossible WM 13.11 0.0014 PDGFRA hCV22271841 CARE Case/Control F MI/SD/NFMI Cleaner WM 11.59 0.003 PEMT hCV7443062 W Case/Control F MI/SD/NF MIAll Possible WM 6.76 0.034 PLAB hCV7494810 CARE Case/Control F MI/SD/NFMI Cleaner WM 7.12 0.0284 PNN hCV2092598 CARE Prospective F MI/SD/NF MIAll Possible WM 6.41 0.0405 PNN hCV2092598 CARE Prospective F MI/SD/NFMI Cleaner WM 10.31 0.0058 PNN hCV2092598 CARE Case/Control F MI/SD/NFMI All Possible WM 6.28 0.0433 PNN hCV2092598 CARE Case/Control FMI/SD/NF MI Cleaner WM 7.25 0.0267 PRKCQ hCV15954277 CARE Prospective FMI/SD/NF MI All Possible WM 6.97 0.0306 PRKCQ hCV15954277 CARECase/Control F MI/SD/NF MI All Possible WM 6.96 0.0308 PRKCQ hCV15954277W Case/Control F MI/SD/NF MI All Possible WM 6.73 0.0345 PRKCQhCV15954277 W Case/Control F MI/SD/NF MI Cleaner WM 6.87 0.0323SERPINA10 hCV1260411 CARE Case/Control F MI/SD/NF MI Cleaner WM 7.970.0185 SERPINA10 hCV7586197 CARE Prospective F MI/SD/NF MI Cleaner WM7.44 0.0242 SERPINA10 hCV7586197 CARE Case/Control F MI/SD/NF MI CleanerWM 9.39 0.0092 SERPINB8 hCV3023236 W Case/Control F MI/SD/NF MI AllPossible WM 7.05 0.0294 SERPINB8 hCV3023236 W Case/Control F MI/SD/NF MICleaner WM 7.62 0.0221 SERPINI2 hCV370782 CARE Prospective F MI/SD/NF MICleaner WM 7.6 0.0223 TAP1 hCV549926 CARE Prospective F MI/SD/NF MI AllPossible WM 8.24 0.0163 TAP1 hCV549926 CARE Case/Control F MI/SD/NF MIAll Possible WM 7.02 0.0299 TAP2 hCV16171128 CARE Prospective F MI/SD/NFMI All Possible WM 8.82 0.0121 TAP2 hCV16171128 CARE Prospective FMI/SD/NF MI Cleaner WM 6.24 0.0441 TAP2 hCV16171128 CARE Case/Control FMI/SD/NF MI All Possible WM 10.07 0.0065 TAP2 hCV16171128 CARECase/Control F MI/SD/NF MI Cleaner WM 7.13 0.0282 THBD hCV2531431 CAREProspective F MI/SD/NF MI All Possible WM 7.8 0.0202 THBD hCV2531431CARE Case/Control F MI/SD/NF MI All Possible WM 7.13 0.0283 TLR6hCV25615380 CARE Prospective F MI/SD/NF MI All Possible WM 5.81 0.0159TLR6 hCV25615380 CARE Prospective F MI/SD/NF MI Cleaner WM 6.24 0.0125TLR6 hCV25615380 CARE Case/Control F MI/SD/NF MI All Possible WM 4.880.0272 VTN hCV2536595 CARE Prospective F MI/SD/NF MI All Possible WM8.83 0.0121 VTN hCV2536595 CARE Prospective F MI/SD/NF MI Cleaner WM7.52 0.0233 VTN hCV2536595 CARE Case/Control F MI/SD/NF MI All PossibleWM 9.52 0.0086 VTN hCV2536595 CARE Case/Control F MI/SD/NF MI Cleaner WM7.01 0.0301 ABCA1 hCV2741083 CARE Prospective F&NF MI All Possible WM9.64 0.0081 ABCA1 hCV2741083 CARE Prospective F&NF MI Cleaner WM 10.640.0049 ABCA1 hCV2741083 CARE Case/Control F&NF MI All Possible WM 10.010.0067 ABCA1 hCV2741083 CARE Case/Control F&NF MI Cleaner WM 9.66 0.008ADAM12 hCV25926318 CARE Prospective F&NF MI All Possible WM 6.32 0.0424ADAM12 hCV25926933 CARE Prospective F&NF MI All Possible WM 6.53 0.0383ADAM12 hCV25926933 CARE Case/Control F&NF MI All Possible WM 6.12 0.0469APOB hCV3216558 CARE Prospective F&NF MI All Possible WM 6.09 0.0477APOB hCV3216558 CARE Case/Control F&NF MI All Possible WM 7.23 0.0269APOB hCV3216558 CARE Case/Control F&NF MI Cleaner WM 7.05 0.0295 APOBhCV7615376 CARE Prospective F&NF MI All Possible WM 6.04 0.0489 APOBhCV7615376 CARE Case/Control F&NF MI All Possible WM 7.21 0.0272 APOBhCV7615376 CARE Case/Control F&NF MI Cleaner WM 7.02 0.0299 ASAH1hCV2442143 CARE Prospective F&NF MI All Possible WM 8.56 0.0138 ASAH1hCV2442143 CARE Prospective F&NF MI Cleaner WM 9.54 0.0085 ASAH1hCV2442143 CARE Case/Control F&NF MI All Possible WM 10.55 0.0051 ASAH1hCV2442143 CARE Case/Control F&NF MI Cleaner WM 11.9 0.0026 ATF6hCV25631989 CARE Prospective F&NF MI All Possible WM 10.47 0.0053 ATF6hCV25631989 CARE Prospective F&NF MI Cleaner WM 10.92 0.0043 ATF6hCV25631989 CARE Case/Control F&NF MI All Possible WM 9.23 0.0099 ATF6hCV25631989 CARE Case/Control F&NF MI Cleaner WM 10.79 0.0045 BAIAP3hCV2503034 CARE Prospective F&NF MI All Possible WM 6.1 0.0473 BAIAP3hCV2503034 CARE Prospective F&NF MI Cleaner WM 7.83 0.02 BCL2A1hCV25992796 CARE Prospective F&NF MI All Possible WM 6.14 0.0465 BCL2A1hCV7509650 CARE Prospective F&NF MI All Possible WM 7.14 0.0281 BCL2A1hCV7509650 CARE Prospective F&NF MI Cleaner WM 6.17 0.0458 BCL2A1hCV7509654 CARE Prospective F&NF MI All Possible WM 6.87 0.0322 BHMThCV11646606 CARE Case/Control F&NF MI Cleaner WM 6.43 0.0402 CASP1hCV16276495 CARE Prospective F&NF MI All Possible WM 11.61 0.0007 CASP1hCV16276495 CARE Prospective F&NF MI Cleaner WM 9.79 0.0018 CASP1hCV16276495 CARE Case/Control F&NF MI All Possible WM 8.04 0.0046 CASP1hCV16276495 CARE Case/Control F&NF MI Cleaner WM 7.41 0.0065 CCKBRhCV9604851 CARE Prospective F&NF MI All Possible WM 8.95 0.0114 CCKBRhCV9604851 CARE Prospective F&NF MI Cleaner WM 8.69 0.0129 CCKBRhCV9604851 CARE Case/Control F&NF MI All Possible WM 7.77 0.0206 CCL22hCV3268420 CARE Prospective F&NF MI All Possible WM 8.64 0.0133 CCL22hCV3268420 CARE Case/Control F&NF MI All Possible WM 8.57 0.0138 CCRL2hCV25637309 CARE Prospective F&NF MI Cleaner WM 6.63 0.0362 CD2hCV2820518 CARE Prospective F&NF MI All Possible WM 6.04 0.0487 CD6hCV2553030 W Case/Control F&NF MI All Possible WM 7.21 0.0272 CD6hCV2553030 W Case/Control F&NF MI Cleaner WM 7.94 0.0189 CD86hCV22271672 CARE Case/Control F&NF MI All Possible WM 6.69 0.0353 CD86hCV22271672 CARE Case/Control F&NF MI Cleaner WM 6.67 0.0356 CELhCV2603661 CARE Prospective F&NF MI Cleaner WM 8.65 0.0132 CELhCV2603661 CARE Case/Control F&NF MI Cleaner WM 6.84 0.0327 COL6A2hCV2811372 CARE Prospective F&NF MI All Possible WM 7.59 0.0225 COL6A2hCV2811372 CARE Prospective F&NF MI Cleaner WM 7.01 0.0301 COL6A2hCV2811372 CARE Case/Control F&NF MI All Possible WM 6.77 0.0339 CR1hCV25598594 CARE Prospective F&NF MI Cleaner WM 4.45 0.0348 CTSBhCV8339791 CARE Prospective F&NF MI All Possible WM 6.14 0.0465 CTSBhCV8339791 CARE Case/Control F&NF MI All Possible WM 7.14 0.0282 CX3CR1hCV7900503 CARE Prospective F&NF MI All Possible WM 9.79 0.0075 CX3CR1hCV7900503 CARE Prospective F&NF MI Cleaner WM 10.67 0.0048 CX3CR1hCV7900503 CARE Case/Control F&NF MI All Possible WM 10.08 0.0065 ELNhCV1253630 CARE Prospective F&NF MI All Possible WM 7.22 0.0271 ELNhCV1253630 CARE Prospective F&NF MI Cleaner WM 6.32 0.0423 ELNhCV1253630 CARE Case/Control F&NF MI All Possible WM 9.48 0.0088 ELNhCV1253630 CARE Case/Control F&NF MI Cleaner WM 7.07 0.0291 F7 hCV783184W Case/Control F&NF MI Cleaner WM 6.3 0.0427 GAPD hCV8921288 CAREProspective F&NF MI All Possible WM 6.53 0.0381 GAPD hCV8921288 CAREProspective F&NF MI Cleaner WM 6.72 0.0348 GBA hCV2276802 CAREProspective F&NF MI Cleaner WM 5.62 0.0178 HLA-A hCV11689916 CAREProspective F&NF MI All Possible WM 6.56 0.0376 HLA-DPB1 hCV11916894CARE Prospective F&NF MI All Possible WM 8.22 0.0164 HLA-DPB1hCV11916894 CARE Prospective F&NF MI Cleaner WM 12.07 0.0024 HLA-DPB1hCV11916894 CARE Case/Control F&NF MI Cleaner WM 10.06 0.0066 HLA-DPB1hCV25651174 CARE Prospective F&NF MI Cleaner WM 7.1 0.0288 HLA-DPB1hCV25651174 CARE Case/Control F&NF MI Cleaner WM 6.54 0.0379 HLA-DPB1hCV8851065 CARE Prospective F&NF MI Cleaner WM 6.52 0.0384 HMMRhCV990335 CARE Prospective F&NF MI All Possible WM 6.09 0.0476 HMOX1hCV15869716 CARE Prospective F&NF MI Cleaner WM 4.64 0.0312 HSPG2hCV1603656 W Case/Control F&NF MI All Possible WM 10.29 0.0058 HSPG2hCV1603656 W Case/Control F&NF MI Cleaner WM 9.02 0.011 HSPG2hCV16172339 CARE Prospective F&NF MI All Possible WM 6.07 0.0482 ICAM1hCV8726331 CARE Prospective F&NF MI All Possible WM 7.01 0.03 IL1AhCV9546471 W Case/Control F&NF MI All Possible WM 9.27 0.0097 IL1AhCV9546471 W Case/Control F&NF MI Cleaner WM 8.88 0.0118 IL1B hCV9546517W Case/Control F&NF MI All Possible WM 7.43 0.0243 IL1B hCV9546517 WCase/Control F&NF MI Cleaner WM 6.85 0.0326 IL4R hCV2769554 CAREProspective F&NF MI All Possible WM 7.2 0.0273 IL4R hCV2769554 CARECase/Control F&NF MI All Possible WM 8.7 0.0129 IL4R hCV2769554 CARECase/Control F&NF MI Cleaner WM 6.46 0.0395 ITGA9 hCV25644901 CAREProspective F&NF MI Cleaner WM 6.25 0.0124 ITPR3 hCV1923359 CAREProspective F&NF MI All Possible WM 9.56 0.0084 ITPR3 hCV1923359 CAREProspective F&NF MI Cleaner WM 7.18 0.0276 ITPR3 hCV1923359 CARECase/Control F&NF MI All Possible WM 8.95 0.0114 ITPR3 hCV1923359 CARECase/Control F&NF MI Cleaner WM 7.28 0.0262 KIAA0329 hCV25751017 CAREProspective F&NF MI All Possible WM 7.15 0.0075 KIAA0329 hCV25751017CARE Prospective F&NF MI Cleaner WM 6.66 0.0099 KLK14 hCV16044337 CAREProspective F&NF MI All Possible WM 13.25 0.0013 KLK14 hCV16044337 CAREProspective F&NF MI Cleaner WM 10.92 0.0043 KLK14 hCV16044337 CARECase/Control F&NF MI All Possible WM 15.27 0.0005 KLK14 hCV16044337 CARECase/Control F&NF MI Cleaner WM 13.84 0.001 LPA hCV11225994 CAREProspective F&NF MI Cleaner WM 6.11 0.0471 LPA hCV11225994 CARECase/Control F&NF MI All Possible WM 7.16 0.0279 LPA hCV11225994 CARECase/Control F&NF MI Cleaner WM 7.07 0.0291 LRP2 hCV16165996 WCase/Control F&NF MI All Possible WM 7.52 0.0233 LRP2 hCV16165996 WCase/Control F&NF MI Cleaner WM 9.39 0.0091 LRP2 hCV25646316 CAREProspective F&NF MI All Possible WM 8.21 0.0165 LRP2 hCV25646316 CARECase/Control F&NF MI All Possible WM 13.74 0.001 LRP2 hCV25646316 CARECase/Control F&NF MI Cleaner WM 7.76 0.0207 LTA hCV7514870 CAREProspective F&NF MI Cleaner WM 6.1 0.0474 MARK3 hCV25926771 CAREProspective F&NF MI All Possible WM 4.41 0.0358 MARK3 hCV25926771 CAREProspective F&NF MI Cleaner WM 4.17 0.0413 MOIR hCV11951095 CAREProspective F&NF MI Cleaner WM 6.02 0.0141 MMP8 hCV11482579 CARECase/Control F&NF MI Cleaner WM 6.47 0.0394 NOS2A hCV11889257 CAREProspective F&NF MI All Possible WM 6.97 0.0306 NOS2A hCV11889257 CAREProspective F&NF MI Cleaner WM 7.1 0.0288 NOS2A hCV11889257 CARECase/Control F&NF MI All Possible WM 7.06 0.0294 NOS2A hCV11889257 CARECase/Control F&NF MI Cleaner WM 6.77 0.0339 NPC1 hCV25472673 CAREProspective F&NF MI All Possible WM 6.88 0.032 NPC1 hCV25472673 CAREProspective F&NF MI Cleaner WM 12.1 0.0024 NPC1 hCV25472673 CARECase/Control F&NF MI Cleaner WM 9.57 0.0084 PDGFRA hCV22271841 CAREProspective F&NF MI All Possible WM 11.91 0.0026 PDGFRA hCV22271841 CAREProspective F&NF MI Cleaner WM 11.14 0.0038 PDGFRA hCV22271841 CARECase/Control F&NF MI All Possible WM 10.59 0.005 PDGFRA hCV22271841 CARECase/Control F&NF MI Cleaner WM 9.62 0.0081 PLA2G4C hCV25472687 CAREProspective F&NF MI All Possible WM 7.04 0.0296 PLA2G4C hCV25472687 CAREProspective F&NF MI Cleaner WM 7.72 0.0211 PLA2G4C hCV25472687 CARECase/Control F&NF MI All Possible WM 7.71 0.0212 PLA2G4C hCV25472687CARE Case/Control F&NF MI Cleaner WM 9.59 0.0083 PLAB hCV7494817 CARECase/Control F&NF MI All Possible WM 6.68 0.0354 PLAT hCV3212009 CAREProspective F&NF MI Cleaner WM 6.49 0.039 PNN hCV2092598 CAREProspective F&NF MI Cleaner WM 9.41 0.0091 PNN hCV2092598 CARECase/Control F&NF MI Cleaner WM 7.58 0.0226 PPOX hCV25652722 CAREProspective F&NF MI All Possible WM 4.35 0.0369 SELL hCV16172571 CAREProspective F&NF MI All Possible WM 7.88 0.0195 SELL hCV25474627 CAREProspective F&NF MI All Possible WM 7.77 0.0206 SERPINA10 hCV1260411CARE Case/Control F&NF MI Cleaner WM 7.34 0.0255 SERPINA10 hCV7586197CARE Prospective F&NF MI Cleaner WM 7.92 0.019 SERPINA10 hCV7586197 CARECase/Control F&NF MI Cleaner WM 9.49 0.0087 SERPINB8 hCV3023236 CARECase/Control F&NF MI All Possible WM 6.02 0.0494 SERPINB8 hCV3023236 WCase/Control F&NF MI All Possible WM 8.74 0.0126 SERPINB8 hCV3023236 WCase/Control F&NF MI Cleaner WM 9.25 0.0098 SERPINI2 hCV370782 CAREProspective F&NF MI All Possible WM 9.92 0.007 SERPINI2 hCV370782 CAREProspective F&NF MI Cleaner WM 9.85 0.0072 SERPINI2 hCV370782 CARECase/Control F&NF MI All Possible WM 8.97 0.0113 SERPINI2 hCV370782 CARECase/Control F&NF MI Cleaner WM 7.53 0.0231 SPARCL1 hCV8827241 CAREProspective F&NF MI Cleaner WM 7.97 0.0186 SPARCL1 hCV8827241 CARECase/Control F&NF MI All Possible WM 6.39 0.0409 SPARCL1 hCV8827241 CARECase/Control F&NF MI Cleaner WM 9.31 0.0095 SPON2 hCV22275550 CAREProspective F&NF MI All Possible WM 6.24 0.0442 SPON2 hCV22275550 CARECase/Control F&NF MI All Possible WM 7.02 0.0299 SREBF2 hCV16170982 CARECase/Control F&NF MI All Possible WM 7.05 0.0295 TAP2 hCV16171128 CAREProspective F&NF MI All Possible WM 6.3 0.043 TAP2 hCV16171128 CARECase/Control F&NF MI All Possible WM 9.16 0.0103 TNF hCV7514879 CAREProspective F&NF MI Cleaner WM 6.72 0.0347 TNF hCV7514879 CARECase/Control F&NF MI Cleaner WM 6.42 0.0404 TRPC6 hCV288790 CAREProspective F&NF MI All Possible WM 7.86 0.0196 TRPC6 hCV288790 CAREProspective F&NF MI Cleaner WM 6.13 0.0465 TRPC6 hCV288790 CARECase/Control F&NF MI All Possible WM 8.04 0.018 VTN hCV2536595 CAREProspective F&NF MI All Possible WM 11.17 0.0037 VTN hCV2536595 CAREProspective F&NF MI Cleaner WM 9.26 0.0097 VTN hCV2536595 CARECase/Control F&NF MI All Possible WM 10.93 0.0042 VTN hCV2536595 CARECase/Control F&NF MI Cleaner WM 8.34 0.0154 SNP Effect Placebo PatientsOdds Ratio (95% CI) Signi- Stati- p- n/total (%) 2 Rare Alleles vs. 1Rare Allele vs. ficance Public stic value 0 Rare Alleles 1 Rare Allele 2Rare Alleles 0 Rare Alleles 0 Rare Alleles Level ABCA1 6.11 0.047113/927 (12.2%) 17/253 (6.7%) 1/14 (7.1%) 0.55 (0.03 to 2.82) 0.52 (0.30to 0.86) P < = 0.05 ABCA1 7.47 0.0239 113/575 (19.7%) 17/165 (10.3%) 1/5(20.0%) 1.02 (0.05 to 6.99) 0.47 (0.26 to 0.79) P < = 0.05 ABCA1 11.080.0256 113/916 (12.3%) 17/243 (7.0%) 1/13 (7.7%) 0.54 (0.07 to 4.27)0.46 (0.26 to 0.81) P < = 0.05 ABCA1 12.38 0.0148 143/604 (23.7%) 60/195(30.8%) 7/15 (46.7%) 2.97 (1.05 to 8.44) 1.44 (1.00 to 2.06) P < = 0.05ABCA1 10.53 0.0324 113/572 (19.8%) 17/159 (10.7%) 1/5 (20.0%) 0.88 (0.10to 8.16) 0.44 (0.24 to 0.79) P < = 0.05 ABCA1 11.04 0.0261 143/531(26.9%) 60/173 (34.7%) 7/15 (46.7%) 2.49 (0.87 to 7.10) 1.46 (1.01 to2.12) P < = 0.05 ABO 9.54 0.049 86/436 (19.7%) 43/262 (16.4%) 2/37(5.4%) 0.19 (0.04 to 0.81) 0.81 (0.53 to 1.24) P < = 0.05 ABO 9.97 0.04186/675 (12.7%) 43/431 (10.0%) 2/59 (3.4%) 0.23 (0.05 to 0.97) 0.75 (0.50to 1.11) P < = 0.05 ABO 10.21 0.0371 86/430 (20.0%) 43/260 (16.5%) 2/39(5.1%) 0.17 (0.04 to 0.74) 0.81 (0.53 to 1.24) P < = 0.05 ABO 9.940.0414 86/434 (19.8%) 43/263 (16.3%) 2/38 (5.3%) 0.18 (0.04 to 0.80)0.80 (0.52 to 1.22) P < = 0.05 ADAMTS1 12.25 0.0156 67/695 (9.6%) 51/406(12.6%) 12/67 (17.9%) 2.08 (1.04 to 4.16) 1.47 (0.99 to 2.19) P < = 0.05ADAMTS1 11.88 0.0183 67/434 (15.4%) 51/258 (19.8%) 12/42 (28.6%) 2.30(1.08 to 4.87) 1.44 (0.95 to 2.17) P < = 0.05 ADAMTS1 5.85 0.0536 67/439(15.3%) 52/263 (19.8%) 12/42 (28.6%) 2.22 (1.05 to 4.46) 1.37 (0.91 to2.04) P < = 0.05 ADAMTS1 12.91 0.0117 67/696 (9.6%) 52/410 (12.7%) 12/67(17.9%) 2.08 (1.04 to 4.17) 1.51 (1.02 to 2.24) P < = 0.05 ADAMTS1 12.830.0121 67/435 (15.4%) 52/258 (20.2%) 12/42 (28.6%) 2.30 (1.09 to 4.87)1.50 (0.99 to 2.27) P < = 0.05 APOB 6.22 0.0126 129/1169 (11.0%)2/4(50.0%) 0/0 (0.0%) 13.40 (1.74 to P < = 0.05 102.88) APOB 9.56 0.048691/455 (20.0%) 35/246 (14.2%) 5/30 (16.7%) 0.76 (0.28 to 2.09) 0.57(0.37 to 0.89) P < = 0.05 APOB 9.51 0.0496 91/455 (20.0%) 35/247 (14.2%)5/29 (17.2%) 0.78 (0.28 to 2.16) 0.57 (0.36 to 0.89) P < = 0.05 ASAH1 70.0302 43/196 (21.9%) 67/364 (18.4%) 21/181 (11.6%) 0.47 (0.26 to 0.81)0.80 (0.52 to 1.24) P < = 0.05 ASAH1 11.92 0.018 43/314 (13.7%) 67/577(11.6%) 21/279 (7.5%) 0.45 (0.26 to 0.80) 0.84 (0.56 to 1.28) P < = 0.05ASAH1 12.44 0.0144 43/195 (22.1%) 67/357 (18.8%) 21/180 (11.7%) 0.40(0.22 to 0.73) 0.92 (0.59 to 1.43) P < = 0.05 ATF6 6.56 0.0376 113/606(18.6%) 11/115 (9.6%) 1/2 (50.0%) 4.36 (0.17 to 110.78) 0.46 (0.23 to0.85) P < = 0.05 ATF6 10.59 0.0315 113/599 (18.9%) 11/113 (9.7%) 1/2(50.0%) 7.21 (0.44 to 119.14) 0.47 (0.24 to 0.93) P < = 0.05 BAIAP3 7.030.0298 98/956 (10.3%) 29/223 (13.0%) 3/7 (42.9%) 6.57 (1.28 to 30.19)1.31 (0.83 to 2.01) P < = 0.05 BAIAP3 8.48 0.0144 98/609 (16.1%) 29/123(23.6%) 3/5 (60.0%) 7.82 (1.28 to 59.95) 1.61 (0.99 to 2.55) P < = 0.05BAIAP3 10.09 0.0389 98/936 (10.5%) 29/221 (13.1%) 3/7 (42.9%) 6.53 (1.41to 30.18) 1.22 (0.77 to 1.91) P < = 0.05 BAIAP3 11.74 0.0194 98/601(16.3%) 29/122 (23.8%) 3/5 (60.0%) 7.03 (1.13 to 43.86) 1.55 (0.95 to2.52) P < = 0.05 BAT2 6.3 0.0428 81/838 (9.7%) 47/319 (14.7%) 3/37(8.1%) 0.82 (0.20 to 2.36) 1.61 (1.09 to 2.36) P < = 0.05 BAT2 7.360.0253 81/530 (15.3%) 417/196 (24.0%) 3/18 (16.7%) 1.11 (0.25 to 3.45)1.75 (1.16 to 2.61) P < = 0.05 BAT2 8.97 0.0618 81/824 (9.8%) 47/312(15.1%) 3/36 (8.3%) 0.81 (0.24 to 2.73) 1.63 (1.10 to 2.42) P < = 0.05BAT2 9.59 0.0479 81/525 (15.4%) 47/192 (24.5%) 3/18 (16.7%) 0.92 (0.26to 3.33) 1.75 (1.15 to 2.68) P < = 0.05 BDKRB2 5.93 0.0515 59/609 (9.7%)65/481 (13.5%) 7/103 (6.8%) 0.68 (0.28 to 1.44) 1.46 (1.00 to 2.12) P <= 0.05 BDKRB2 6.21 0.0448 59/386 (15.3%) 65/299 (21.7%) 7/59 (11.9%)0.75 (0.30 to 1.62) 1.54 (1.04 to 2.28) P < = 0.05 CAPN2 9.99 0.0405124/442 (28.1%) 67/320 (20.9%) 18/50 (36.0%) 1.38 (0.73 to 2.59) 0.67(0.47 to 0.94) P < = 0.05 CAPN2 11.45 0.022 124/396 (31.3%) 67/281(23.8%) 18/41 (43.9%) 1.68 (0.86 to 3.29) 0.67 (0.47 to 0.95) P < = 0.05CASP1 11.88 0.0006 91/961 (9.5%) 40/228 (17.5%) 0/0 (0.0%) 2.03 (1.35 to3.03) P < = 0.005 CASP1 10.43 0.0012 91/591 (15.4%) 40/149 (26.8%) 0/0(0.0%) 2.02 (1.31 to 3.07) P < = 0.005 CASP1 8.94 0.0028 91/945 (9.6%)40/223 (17.9%) 0/0 (0.0%) 1.90 (1.25 to 2.90) P < = 0.005 CASP1 8.1560.0043 91/585 (15.6%) 40/147 (27.2%) 0/0 (0.0%) 1.92 (1.23 to 3.01) P <= 0.005 CCKBR 10.68 0.0048 121/1058 (11.4%) 7/130 (5.4%) 3/6 (50.0%)7.74 (1.42 to 42.24) 0.44 (0.18 to 0.90) P < = 0.05 CCKBR 8.61 0.0135121/666 (18.2%) 7/74 (9.5%) 3/4 (75.0%) 13.49 (1.71 to 0.47 (0.19 to0.98) P < = 0.05 274.34) CCKBR 14.34 0.0063 121/1038 (11.7%) 7/128(5.5%) 3/6 (50.0%) 6.32 (1.22 to 32.70) 0.41 (0.19 to 0.91) P < = 0.05CCKBR 11.17 0.0248 121/657 (18.4%) 7/74 (9.5%) 3/4 (75.0%) 10.11 (1.03to 99.58) 0.48 (0.21 to 1.09) P < = 0.05 CCL22 6.88 0.032 121/1079(11.2%) 8/112 (7.1%) 2/3 (66.7%) 15.83 (1.51 to 0.61 (0.27 to 1.21) P <= 0.05 341.97) CCL22 11.27 0.0236 121/1059 (11.4%) 8/110 (7.3%) 2/3(66.7%) 19.59 (1.72 to 0.62 (0.29 to 1.32) P < = 0.05 222.63) CCRL210.08 0.0065 105/1029 (10.2%) 21/150 (14.0%) 5/13 (38.5%) 5.50 (1.64 to16.79) 1.43 (0.85 to 2.33) P < = 0.005 CCRL2 7.69 0.0214 105/637 (16.5%)21/96 (21.9%) 5/10 (50.0%) 5.07 (1.39 to 18.51) 1.42 (0.82 to 2.37) P <= 0.05 CCRL2 15.11 0.0045 105/1011 (10.4%) 21/146 (14.4%) 5/13 (38.5%)6.60 (2.07 to 21.11) 1.28 (0.76 to 2.16) P < = 0.005 CCRL2 9.24 0.0555105/629 (16.7%) 21/95 (22.1%) 5/10 (50.0%) 4.81 (1.34 to 17.26) 1.15(0.66 to 2.00) P < = 0.05 CCRL2 5.95 0.0509 50/258 (19.4%) 67/349(19.2%) 14/136 (10.3%) 0.48 (0.25 to 0.88) 0.99 (0.66 to 1.49) P < =0.05 COL2A1 7.59 0.1079 113/1042 (10.8%) 16/126 (12.7%) 2/5 (40.0%) 8.26(1.11 to 61.51) 1.18 (0.67 to 2.09) P < = 0.05 CPT1A 7.1 0.0288 116/1019(11.4%) 12/169 (7.1%) 2/4 (50.0%) 7.78 (0.93 to 65.35) 0.59 (0.31 to1.06) P < = 0.05 CR1 5.01 0.0253 119/1105 (10.8%) 11/62 (17.7%) 0/0(0.0%) 2.25 (1.11 to 4.57) P < = 0.05 CR1 5.66 0.0173 119/693 (17.2%)11/38 (28.9%) 0/0 (0.0%) 2.56 (1.18 to 5.57) P < = 0.05 CX3CR1 7.750.0208 78/587 (13.3%) 41/507 (8.1%) 12/92 (13.0%) 0.98 (0.49 to 1.82)0.57 (0.38 to 0.85) P < = 0.05 CX3CR1 8.04 0.018 78/380 (20.5%) 41/311(13.2%) 12/48 (25.0%) 1.29 (0.62 to 2.53) 0.59 (0.39 to 0.88) P < = 0.05CX3CR1 9.56 0.0484 78/577 (13.5%) 41/497 (8.2%) 12/90 (13.3%) 1.11 (0.57to 2.16) 0.59 (0.39 to 0.89) P < = 0.05 CX3CR1 9.06 0.0597 78/376(20.7%) 41/306 (13.4%) 12/48 (25.0%) 1.53 (0.75 to 3.13) 0.65 (0.42 to0.99) P < = 0.05 DBH 11.92 0.018 118/634 (18.6%) 10/93 (10.8%) 3/6(50.0%) 6.23 (1.19 to 32.65) 0.53 (0.26 to 1.09) P < = 0.05 F7 9.660.0466 178/659 (27.0%) 28/146 (19.2%) 6/14 (42.9%) 1.99 (0.67 to 5.88)0.62 (0.40 to 0.97) P < = 0.05 F7 9.86 0.0428 178/579 (30.7%) 28/132(21.2%) 6/13 (46.2%) 1.84 (0.60 to 5.61) 0.59 (0.37 to 0.94) P < = 0.05GBA 6.95 0.0084 45/189 (23.8%) 85/555 (15.3%) 0/0 (0.0%) 0.58 (0.39 to0.87) P < = 0.05 HLA-A 6.38 0.0412 33/404 (8.2%) 42/381 (11.0%) 49/351(14.0%) 1.82 (1.15 to 2.93) 1.39 (0.86 to 2.26) P < = 0.05 HLA-A 9.440.0511 33/399 (8.3%) 42/371 (11.3%) 49/345 (14.2%) 1.76 (1.10 to 2.82)1.20 (0.73 to 1.97) P < = 0.05 HLA-DPB1 6.56 0.0377 92/932 (9.9%) 38/245(15.5%) 1/16 (6.3%) 0.61 (0.03 to 3.06) 1.68 (1.10 to 2.50) P < = 0.05HLA-DPB1 10.26 0.0059 92/591 (15.6%) 38/141 (27.0%) 1/10 (10.0%) 0.60(0.03 to 3.26) 2.00 (1.29 to 3.07) P < = 0.05 HLA-DPB1 11.82 0.018792/584 (15.8%) 38/139 (27.3%) 1/10 (10.0%) 0.74 (0.09 to 6.02) 1.97(1.25 to 3.10) P < = 0.05 HLA-DPB1 6.51 0.0386 71/370 (19.2%) 56/300(18.7%) 4/69 (5.8%) 0.26 (0.08 to 0.65) 0.97 (0.65 to 1.42) P < = 0.05HLA-DPB1 8.92 0.0631 71/368 (19.3%) 56/295 (19.0%) 4/67 (6.0%) 0.26(0.09 to 0.76) 0.97 (0.65 to 1.45) P < = 0.05 HLA-DPB1 6.07 0.048 72/391(18.4%) 56/294 (19.0%) 3/60 (5.0%) 0.23 (0.06 to 0.65) 1.04 (0.71 to1.53) P < = 0.05 HSPG2 7.98 0.0924 174/665 (26.2%) 31/133 (23.3%) 5/7(71.4%) 6.06 (1.16 to 31.62) 0.88 (0.56 to 1.37) P < = 0.05 HSPG2 7.850.0974 174/589 (29.5%) 31/117 (26.5%) 5/6 (83.3%) 10.41 (1.21 to 89.65)0.89 (0.56 to 1.39) P < = 0.05 IL1A 13.48 0.0092 121/400 (30.3%) 78/351(22.2%) 11/61 (18.0%) 0.52 (0.26 to 1.04) 0.67 (0.48 to 0.93) P < = 0.05IL1A 14.02 0.0072 121/354 (34.2%) 78/307 (25.4%) 11/56 (19.6%) 0.49(0.24 to 0.98) 0.67 (0.47 to 0.94) P < = 0.05 IL1B 11.13 0.0252 65/427(15.2%) 56/257 (21.8%) 10/50 (20.0%) 1.64 (0.76 to 3.53) 1.64 (1.09 to2.47) P < = 0.05 IL1RL1 9.2 0.0101 49/451 (10.9%) 50/556 (9.0%) 32/187(17.1%) 1.69 (1.04 to 2.73) 0.81 (0.53 to 1.23) P < = 0.05 IL1RL1 100.0404 49/443 (11.1%) 50/545 (9.2%) 32/184 (17.4%) 1.86 (1.13 to 3.08)0.84 (0.55 to 1.29) P < = 0.05 IL1RL1 7.99 0.0919 49/281 (17.4%) 50/326(15.3%) 32/127 (25.2%) 1.85 (1.09 to 3.14) 0.94 (0.60 to 1.46) P < =0.05 IL4R 7.89 0.0194 42/371 (11.3%) 73/564 (12.9%) 16/257 (6.2%) 0.52(0.28 to 0.93) 1.16 (0.78 to 1.76) P < = 0.05 IL4R 6.82 0.0331 42/233(18.0%) 73/358 (20.4%) 16/151 (10.6%) 0.54 (0.28 to 0.98) 1.16 (0.77 to1.79) P < = 0.05 IL4R 10.12 0.0384 42/361 (11.6%) 73/557 (13.1%) 16/252(6.3%) 0.46 (0.25 to 0.84) 1.14 (0.75 to 1.73) P < = 0.05 IL4R 8.560.0732 42/230 (18.3%) 73/354 (20.6%) 16/149 (10.7%) 0.49 (0.26 to 0.92)1.16 (0.75 to 1.80) P < = 0.05 ITGA9 10.71 0.0011 107/665 (16.1%) 24/76(31.6%) 0/0 (0.0%) 2.41 (1.40 to 4.03) P < = 0.005 KIAA0329 6.62 0.0101113/1102 (10.3%) 13/62 (21.0%) 0/0 (0.0%) 2.32 (1.18 to 4.29) P < = 0.05KIAA0329 6.42 0.0113 113/687 (16.4%) 13/40 (32.5%) 0/0 (0.0%) 2.45 (1.19to 4.80) P < = 0.05 KLK14 11.5 0.0032 50/560 (8.9%) 57/511 (11.2%)23/115 (20.0%) 2.55 (1.46 to 4.34) 1.28 (0.86 to 1.92) P < = 0.005 KLK1410.11 0.0064 50/342 (14.6%) 57/323 (17.6%) 23/76 (30.3%) 2.53 (1.41 to4.47) 1.25 (0.83 to 1.90) P < = 0.05 KLK14 18.35 0.0011 50/549 (9.1%)57/502 (11.4%) 23/113 (20.4%) 2.79 (1.57 to 4.94) 1.29 (0.85 to 1.96) P< = 0.005 KLK14 17.46 0.0016 50/339 (14.7%) 57/318 (17.9%) 23/75 (30.7%)2.86 (1.56 to 5.26) 1.30 (0.85 to 2.01) P < = 0.005 KLKB1 6.44 0.039927/311 (8.7%) 61/592 (10.3%) 43/288 (14.9%) 1.85 (1.11 to 3.11) 1.21(0.76 to 1.97) P < = 0.05 KLKB1 10.02 0.04 27/308 (8.8%) 61/578 (10.6%)43/283 (15.2%) 1.94 (1.15 to 3.28) 1.19 (0.73 to 1.93) P < = 0.05 KLKB110.73 0.0298 27/197 (13.7%) 61/349 (17.5%) 43/188 (22.9%) 1.97 (1.13 to3.40) 1.32 (0.79 to 2.21) P < = 0.05 LAPTM5 7.11 0.0286 62/694 (8.9%)59/418 (14.1%) 7/64 (10.9%) 1.25 (0.50 to 2.69) 1.68 (1.15 to 2.45) P <= 0.05 LAPTM5 11.11 0.0254 62/681 (9.1%) 59/409 (14.4%) 7/64 (10.9%)1.29 (0.55 to 3.01) 1.71 (1.16 to 2.53) P < = 0.05 LRP2 5.2 0.074382/431 (19.0%) 47/265 (17.7%) 2/47 (4.3%) 0.19 (0.03 to 0.63) 0.92 (0.61to 1.36) P < = 0.05 LRP2 9.65 0.0468 121/469 (25.8%) 64/283 (22.6%)25/63 (39.7%) 1.95 (1.12 to 3.38) 0.87 (0.61 to 1.24) P < = 0.05 LRP27.77 0.1003 82/427 (19.2%) 47/260 (18.1%) 2/47 (4.3%) 0.19 (0.04 to0.81) 0.95 (0.63 to 1.44) P < = 0.05 LRP2 11.4 0.0224 121/426 (28.4%)64/241 (26.6%) 25/54 (46.3%) 2.35 (1.30 to 4.22) 0.95 (0.66 to 1.36) P <= 0.05 LTA 6.27 0.0434 45/532 (8.5%) 69/536 (12.9%) 17/124 (13.7%) 1.72(0.93 to 3.07) 1.60 (1.08 to 2.39) P < = 0.05 LTA 7.24 0.0268 45/334(13.5%) 69/330 (20.9%) 17/78 (21.8%) 1.79 (0.94 to 3.29) 1.70 (1.13 to2.57) P < = 0.05 LTA 14.18 0.0068 45/521 (8.6%) 69/527 (13.1%) 17/122(13.9%) 1.87 (1.02 to 3.45) 1.62 (1.08 to 2.42) P < = 0.05 LTA 12.70.0129 45/329 (13.7%) 69/328 (21.0%) 17/76 (22.4%) 1.90 (0.99 to 3.64) P< = 0.05 MARK3 3.93 0.0473 39/453 (8.6%) 88/713 (12.3%) 0/0 (0.0%) 1.49(1.01 to 2.24) P < = 0.05 MARK3 3.89 0.0485 39/279 (14.0%) 88/446(19.7%) 0/0 (0.0%) 1.51 (1.01 to 2.30) P < = 0.05 MC1R 6.29 0.0121124/655 (18.9%) 7/90 (7.8%) 0/0 (0.0%) 0.36 (0.15 to 0.75) P < = 0.05MMP7 6.66 0.0358 93/739 (12.6%) 37/398 (9.3%) 1/58 (1.7%) 0.12 (0.01 to0.56) 0.71 (0.47 to 1.06) P < = 0.05 MMP7 5.63 0.0599 93/472 (19.7%)37/239 (15.5%) 1/33 (3.0%) 0.13 (0.01 to 0.60) 0.75 (0.49 to 1.12) P < =0.05 MMP7 10.52 0.0325 93/728 (12.8%) 37/389 (9.5%) 1/57 (1.8%) 0.13(0.02 to 0.98) 0.71 (0.47 to 1.08) P < = 0.05 MMP7 10.49 0.0329 93/467(19.9%) 37/236 (15.7%) 1/33 (3.0%) 0.12 (0.02 to 0.88) 0.72 (0.47 to1.11) P < = 0.05 MMP8 6.2 0.045 25/206 (12.1%) 72/353 (20.4%) 34/179(19.0%) 1.70 (0.97 to 3.00) 1.86 (1.15 to 3.08) P < = 0.05 MTR 4.630.0314 118/1131 (10.4%) 12/62 (19.4%) 0/0 (0.0%) 2.06 (1.02 to 3.86) P <= 0.05 MTR 4.01 0.0451 118/702 (16.8%) 12/41 (29.3%) 0/0 (0.0%) 2.05(0.98 to 4.04) P < = 0.05 NDUFS2 3.96 0.0467 128/1186 (10.8%) 3/9(33.3%) 0/0 (0.0%) 4.13 (0.86 to P < = 0.05 15.86) NDUFS2 5.38 0.0204128/1164 (11.0%) 3/9 (33.3%) 0/0 (0.0%) 5.40 (1.30 to P < = 0.05 22.49)NDUFS2 4.11 0.0426 128/729 (17.6%) 3/6 (50.0%) 0/0 (0.0%) 5.41 (1.06 toP < = 0.05 27.68) NOS2A 6.29 0.043 77/785 (9.8%) 51/364 (14.0%) 2/45(4.4%) 0.43 (0.07 to 1.43) 1.50 (1.02 to 2.18) P < = 0.05 NOS2A 6.640.0361 77/486 (15.8%) 51/228 (22.4%) 2/29 (6.9%) 0.39 (0.06 to 1.35)1.53 (1.03 to 2.27) P < = 0.05 NOS2A 10.14 0.0381 77/774 (9.9%) 51/355(14.4%) 2/43 (4.7%) 0.41 (0.10 to 1.75) 1.55 (1.05 to 2.28) P < = 0.05NOS2A 9.62 0.0474 77/482 (16.0%) 51/223 (22.9%) 2/29 (6.9%) 0.35 (0.08to 1.53) 1.51 (1.00 to 2.29) P < = 0.05 NPC1 7.47 0.0239 37/436 (8.5%)65/575 (11.3%) 28/173 (16.2%) 2.08 (1.22 to 3.52) 1.37 (0.90 to 2.12) P< = 0.05 NPC1 12.68 0.0018 37/282 (13.1%) 65/360 (18.1%) 28/95 (29.5%)2.77 (1.57 to 4.84) 1.46 (0.95 to 2.28) P < = 0.005 NPC1 11.66 0.0237/428 (8.6%) 65/567 (11.5%) 28/167 (16.8%) 2.02 (1.17 to 3.48) 1.29(0.84 to 1.98) P < = 0.05 NPC1 16.12 0.0029 37/279 (13.3%) 65/356(18.3%) 28/93 (30.1%) 2.60 (1.45 to 4.69) 1.32 (0.84 to 2.06) P < =0.005 PDGFRA 11.07 0.004 100/944 (10.6%) 26/231 (11.3%) 5/10 (50.0%)8.44 (2.31 to 30.83) 1.07 (0.67 to 1.67) P < = 0.005 PDGFRA 8.72 0.0128100/580 (17.2%) 26/152 (17.1%) 5/7 (71.4%) 11.99 (2.55 to 84.58) 0.99(0.61 to 1.57) P < = 0.005 PDGFRA 13.93 0.0075 100/925 (10.8%) 26/228(11.4%) 5/10 (50.0%) 7.67 (2.13 to 27.62) 1.17 (0.73 to 1.86) P < =0.005 PDGFRA 11.42 0.0222 100/573 (17.5%) 26/150 (17.3%) 5/7 (71.4%)11.06 (2.05 to 59.73) 1.13 (0.69 to 1.84) P < = 0.05 PEMT 12.19 0.01674/235 (31.5%) 84/386 (21.8%) 44/174 (25.3%) 0.76 (0.49 to 1.19) 0.61(0.42 to 0.89) P < = 0.05 PLAB 9.73 0.0452 67/411 (16.3%) 60/278 (21.6%)4/46 (8.7%) 0.48 (0.17 to 1.42) 1.51 (1.02 to 2.25) P < = 0.05 PNN 5.350.0691 110/1043 (10.5%) 18/141 (12.8%) 3/8 (37.5%) 5.09 (1.03 to 21.02)1.24 (0.71 to 2.07) P < = 0.05 PNN 6.48 0.0392 110/655 (16.8%) 18/83(21.7%) 3/4 (75.0%) 14.84 (1.88 to 1.37 (0.76 to 2.36) P < = 0.05301.89) PNN 9.09 0.0589 110/1023 (10.8%) 18/139 (12.9%) 3/8 (37.5%) 5.16(1.17 to 22.86) 1.30 (0.75 to 2.24) P < = 0.05 PNN 8.69 0.0694 110/647(17.0%) 18/82 (22.0%) 3/4 (75.0%) 11.89 (1.16 to 1.32 (0.74 to 2.35) P <= 0.05 121.79) PRKCQ 6.29 0.043 83/657 (12.6%) 45/445 (10.1%) 3/85(3.5%) 0.25 (0.06 to 0.70) 0.78 (0.53 to 1.14) P < = 0.05 PRKCQ 10.690.0302 83/645 (12.9%) 45/437 (10.3%) 3/83 (3.6%) 0.24 (0.07 to 0.80)0.79 (0.53 to 1.17) P < = 0.05 PRKCQ 10.97 0.027 132/442 (29.9%) 66/317(20.8%) 12/53 (22.6%) 0.74 (0.37 to 1.46) 0.64 (0.45 to 0.90) P < = 0.05PRKCQ 11.06 0.0259 132/391 (33.8%) 66/280 (23.6%) 12/47 (25.5%) 0.74(0.37 to 1.49) 0.63 (0.44 to 0.89) P < = 0.05 SERPINA10 11.07 0.025889/536 (16.6%) 41/178 (23.0%) 1/21 (4.8%) 0.28 (0.04 to 2.16) 1.69 (1.10to 2.60) P < = 0.05 SERPINA10 6.8 0.0335 86/537 (16.0%) 41/179 (22.9%)1/24 (4.2%) 0.23 (0.01 to 1.10) 1.56 (1.02 to 2.35) P < = 0.05 SERPINA1012.51 0.0139 86/532 (16.2%) 41/176 (23.3%) 1/23 (4.3%) 0.29 (0.04 to2.20) 1.80 (1.16 to 2.78) P < = 0.05 SERPINB8 13.94 0.0075 56/277(20.2%) 118/405 (29.1%) 36/131 (27.5%) 1.50 (0.92 to 2.43) 1.63 (1.13 to2.36) P < = 0.05 SERPINB8 15.35 0.004 56/2416 (22.8%) 118/360 (32.8%)36/113 (31.9%) 1.62 (0.98 to 2.66) 1.66 (1.14 to 2.42) P < = 0.05SERPINI2 7.46 0.024 45/293 (15.4%) 73/337 (21.7%) 13/112 (11.6%) 0.72(0.36 to 1.36) 1.52 (1.02 to 2.31) P < = 0.05 TAP1 7.77 0.0206 81/829(9.8%) 42/329 (12.8%) 8/33 (24.2%) 2.96 (1.21 to 6.50) 1.35 (0.90 to2.00) P < = 0.05 TAP1 11.77 0.0191 81/817 (9.9%) 42/319 (13.2%) 8/33(24.2%) 2.73 (1.17 to 6.39) 1.36 (0.91 to 2.05) P < = 0.05 TAP2 7.020.0298 106/1001 (10.6%) 21/183 (11.5%) 4/10 (40.0%) 5.63 (1.42 to 20.02)1.09 (0.65 to 1.77) P < = 0.05 TAP2 5.22 0.0735 106/627 (16.9%) 21/108(19.4%) 4/8 (50.0%) 4.92 (1.15 to 21.08) 1.19 (0.69 to 1.96) P < = 0.05TAP2 12.08 0.0168 106/988 (10.7%) 21/176 (11.9%) 4/9 (44.4%) 7.90 (1.80to 34.62) 1.25 (0.75 to 2.08) P < = 0.05 TAP2 9.82 0.0435 106/622(17.0%) 21/105 (20.0%) 4/8 (50.0%) 6.41 (1.32 to 31.22) 1.29 (0.76 to2.21) P < = 0.05 THBD 7.47 0.0239 79/819 (9.6%) 42/325 (12.9%) 9/41(22.0%) 2.63 (1.15 to 5.51) 1.39 (0.93 to 2.06) P < = 0.05 THBD 11.840.0185 79/809 (9.8%) 42/314 (13.4%) 9/40 (22.5%) 2.77 (1.21 to 6.36)1.34 (0.89 to 2.02) P < = 0.05 TLR6 4.74 0.0294 128/1187 (10.8%) 3/8(37.5%) 0/0 (0.0%) 4.97 (1.01 to P < = 0.05 20.47) TLR6 4.6 0.032128/739 (17.3%) 3/5 (60.0%) 0/0 (0.0%) 7.16 (1.18 to P < = 0.05 54.77)TLR6 4.1 0.043 128/1165 (11.0%) 3/8 (37.5%) 0/0 (0.0%) 4.51 (1.05 to P <= 0.05 19.38) VTN 8.57 0.0138 25/361 (6.9%) 74/567 (13.1%) 32/268(11.9%) 1.82 (1.06 to 3.18) 2.02 (1.27 to 3.30) P < = 0.05 VTN 7.350.0254 25/213 (11.7%) 74/357 (20.7%) 32/175 (18.3%) 1.68 (0.96 to 2.99)1.97 (1.22 to 3.26) P < = 0.05 VTN 18.58 0.001 25/352 (7.1%) 74/559(13.2%) 32/263 (12.2%) 1.83 (1.03 to 3.25) 2.16 (1.31 to 3.54) P < =0.05 VTN 13.75 0.0081 25/210 (11.9%) 74/352 (21.0%) 32/174 (18.4%) 1.61(0.89 to 2.91) 1.99 (1.19 to 3.33) P < = 0.05 ABCA1 9.26 0.0097 137/927(14.8%) 19/253 (7.5%) 1/14 (7.1%) 0.44 (0.02 to 2.25) 0.47 (0.28 to0.75) P < = 0.05 ABCA1 10.18 0.0062 137/599 (22.9%) 19/167 (11.4%) 1/5(20.0%) 0.84 (0.04 to 5.76) 0.43 (0.25 to 0.71) P < = 0.005 ABCA1 13.650.0085 137/915 (15.0%) 19/242 (7.9%) 1/13 (7.7%) 0.43 (0.05 to 3.35)0.45 (0.26 to 0.75) P < = 0.05 ABCA1 12.5 0.014 137/595 (23.0%) 19/160(11.9%) 1/5 (20.0%) 0.77 (0.08 to 7.06) 0.43 (0.24 to 0.74) P < = 0.05ADAM12 6.21 0.0449 64/578 (11.1%) 68/482 (14.1%) 20/102 (19.6%) 1.96(1.10 to 3.36) 1.32 (0.92 to 1.90) P < = 0.05 ADAM12 6.41 0.0405 64/578(11.1%) 70/487 (14.4%) 20/102 (19.6%) 1.96 (1.10 to 3.36) 1.35 (0.94 to1.94) P < = 0.05 ADAM12 12.23 0.0157 64/563 (11.4%) 70/481 (14.6%)20/100 (20.0%) 1.94 (1.09 to 3.46) 1.38 (0.95 to 1.99) P < = 0.05 APOB5.98 0.0504 111/732 (15.2%) 43/402 (10.7%) 4/53 (7.5%) 0.46 (0.14 to1.15) 0.67 (0.46 to 0.97) P < = 0.05 APOB 12.04 0.0171 111/721 (15.4%)43/389 (11.1%) 4/53 (7.5%) 0.43 (0.15 to 1.22) 0.64 (0.44 to 0.94) P < =0.05 APOB 11.71 0.0196 111/475 (23.4%) 43/252 (17.1%) 4/29 (13.8%) 0.48(0.16 to 1.44) 0.60 (0.40 to 0.91) P < = 0.05 APOB 5.93 0.0515 111/732(15.2%) 43/403 (10.7%) 4/52 (7.7%) 0.47 (0.14 to 1.17) 0.67 (0.46 to0.97) P < = 0.05 APOB 11.99 0.0174 111/721 (15.4%) 43/390 (11.0%) 4/52(7.7%) 0.43 (0.15 to 1.23) 0.64 (0.43 to 0.94) P < = 0.05 APOB 11.630.0203 111/475 (23.4%) 43/253 (17.0%) 4/28 (14.3%) 0.49 (0.16 to 1.48)0.60 (0.40 to 0.90) P < = 0.05 ASAH1 8.37 0.0152 54/320 (16.9%) 79/588(13.4%) 25/284 (8.8%) 0.48 (0.28 to 0.78) 0.76 (0.53 to 1.12) P < = 0.05ASAH1 9.31 0.0095 54/207 (26.1%) 79/376 (21.0%) 25/185 (13.5%) 0.44(0.26 to 0.74) 0.75 (0.51 to 1.12) P < = 0.05 ASAH1 15.78 0.0033 54/314(17.2%) 79/576 (13.7%) 25/278 (9.0%) 0.43 (0.25 to 0.72) 0.80 (0.55 to1.17) P < = 0.05 ASAH1 15.13 0.0044 54/206 (26.2%) 79/368 (21.5%) 25/183(13.7%) 0.40 (0.23 to 0.69) 0.87 (0.58 to 1.31) P < = 0.005 ATF6 9.020.011 137/982 (14.0%) 13/176 (7.4%) 2/4 (50.0%) 6.17 (0.74 to 51.73)0.49 (0.26 to 0.86) P < = 0.05 ATF6 9.45 0.0089 137/630 (21.7%) 13/117(11.1%) 2/3 (66.7%) 7.20 (0.68 to 155.43) 0.45 (0.23 to 0.80) P < = 0.05ATF6 12.16 0.0162 137/963 (14.2%) 13/171 (7.6%) 2/4 (50.0%) 5.84 (0.81to 42.04) 0.51 (0.28 to 0.93) P < = 0.05 ATF6 13.53 0.0089 137/622(22.0%) 13/114 (11.4%) 2/3 (66.7%) 8.24 (0.72 to 94.43) 0.45 (0.24 to0.84) P < = 0.05 BAIAP3 5.1 0.0782 121/956 (12.7%) 33/223 (14.8%) 3/7(42.9%) 5.18 (1.01 to 23.74) 1.20 (0.78 to 1.80) P < = 0.05 BAIAP3 6.740.0344 121/632 (19.1%) 33/127 (26.0%) 3/5 (60.0%) 6.33 (1.04 to 48.48)1.48 (0.94 to 2.29) P < = 0.05 BCL2A1 6.06 0.0482 102/665 (15.3%) 47/459(10.2%) 9/67 (13.4%) 0.86 (0.39 to 1.70) 0.63 (0.43 to 0.90) P < = 0.05BCL2A1 7.04 0.0296 102/662 (15.4%) 46/463 (9.9%) 9/66 (13.6%) 0.87 (0.39to 1.72) 0.61 (0.42 to 0.87) P < = 0.05 BCL2A1 6.1 0.0475 102/434(23.5%) 46/289 (15.9%) 9/46 (19.6%) 0.79 (0.35 to 1.63) 0.62 (0.42 to0.90) P < = 0.05 BCL2A1 6.79 0.0336 101/645 (15.7%) 48/468 (10.3%) 9/71(12.7%) 0.78 (0.35 to 1.55) 0.62 (0.42 to 0.88) P < = 0.05 BHMT 8.370.0789 72/390 (18.5%) 74/294 (25.2%) 12/75 (16.0%) 0.86 (0.44 to 1.71)1.56 (1.06 to 2.28) P < = 0.05 CASP1 11.32 0.0008 112/961 (11.7%) 46/228(20.2%) 0/0 (0.0%) 1.92 (1.30 to 2.78) P < = 0.005 CASP1 9.59 0.002112/612 (18.3%) 46/155 (29.7%) 0/0 (0.0%) 1.88 (1.25 to 2.80) P < =0.005 CASP1 7.91 0.0049 112/945 (11.9%) 46/221 (20.8%) 0/0 (0.0%) 1.76(1.19 to 2.61) P < = 0.005 CASP1 7.29 0.0069 112/606 (18.5%) 46/151(30.5%) 0/0 (0.0%) 1.79 (1.17 to 2.72) P < = 0.05 CCKBR 7.15 0.028143/1058 (13.5%) 12/130 (9.2%) 3/6 (50.0%) 6.40 (1.17 to 34.86) 0.65(0.33 to 1.16) P < = 0.05 CCKBR 5.9 0.0523 143/688 (20.8%) 12/79 (15.2%)3/4 (75.0%) 11.43 (1.45 to 0.68 (0.34 to 1.25) P < = 0.05 231.99) CCKBR10.61 0.0314 143/1037 (13.8%) 12/127 (9.4%) 3/6 (50.0%) 5.25 (1.03 to26.81) 0.60 (0.32 to 1.12) P < = 0.05 CCL22 5.58 0.0615 145/1079 (13.4%)11/112 (9.8%) 2/3 (66.7%) 12.88 (1.23 to 0.70 (0.35 to 1.28) P < = 0.05278.04) CCL22 8.8 0.0662 145/1057 (13.7%) 11/110 (10.0%) 2/3 (66.7%)13.59 (1.21 to 0.74 (0.38 to 1.42) P < = 0.05 152.36) CCRL2 6.46 0.039655/263 (20.9%) 85/367 (23.2%) 18/140 (12.9%) 0.56 (0.31 to 0.98) 1.14(0.78 to 1.68) P < = 0.05 CD2 5.82 0.0546 144/1018 (14.1%) 13/172 (7.6%)1/4 (25.0%) 2.02 (0.10 to 15.92) 0.50 (0.26 to 0.87) P < = 0.05 CD6 9.820.0435 148/479 (30.9%) 67/288 (23.3%) 17/43 (39.5%) 1.43 (0.74 to 2.75)0.68 (0.48 to 0.95) P < = 0.05 CD6 10.57 0.0319 148/433 (34.2%) 67/263(25.5%) 17/41 (41.5%) 1.35 (0.70 to 2.62) 0.65 (0.46 to 0.91) P < = 0.05CD86 9.04 0.0601 144/996 (14.5%) 11/151 (7.3%) 1/8 (12.5%) 0.90 (0.11 to7.42) 0.42 (0.22 to 0.83) P < = 0.05 CD86 9.27 0.0546 144/646 (22.3%)11/95 (11.6%) 1/6 (16.7%) 0.75 (0.09 to 6.62) 0.41 (0.21 to 0.82) P < =0.05 CEL 8.47 0.0145 97/401 (24.2%) 52/307 (16.9%) 7/60 (11.7%) 0.41(0.17 to 0.88) 0.64 (0.44 to 0.93) P < = 0.05 CEL 12.35 0.0149 97/392(24.7%) 52/305 (17.0%) 7/60 (11.7%) 0.42 (0.18 to 0.98) 0.67 (0.45 to0.99) P < = 0.05 COL6A2 7.44 0.0242 47/278 (16.9%) 84/622 (13.5%) 27/295(9.2%) 0.50 (0.30 to 0.81) 0.77 (0.52 to 1.14) P < = 0.05 COL6A2 6.890.0319 47/184 (25.5%) 84/401 (20.9%) 27/186 (14.5%) 0.49 (0.29 to 0.83)0.77 (0.51 to 1.17) P < = 0.05 COL6A2 12.53 0.0138 47/271 (17.3%) 84/610(13.8%) 27/290 (9.3%) 0.51 (0.30 to 0.85) 0.77 (0.51 to 1.14) P < = 0.05CR1 4.25 0.0392 147/740 (19.9%) 11/31 (35.5%) 0/0 (0.0%) 2.22 (1.01 to4.65) P < = 0.05 CTSB 5.61 0.0604 113/888 (12.7%) 38/281 (13.5%) 7/23(30.4%) 3.00 (1.13 to 7.20) 1.07 (0.72 to 1.58) P < = 0.05 CTSB 10.080.0392 113/870 (13.0%) 38/275 (13.8%) 7/23 (30.4%) 3.35 (1.31 to 8.58)1.13 (0.75 to 1.69) P < = 0.05 CX3CR1 9.61 0.0082 91/587 (15.5%) 50/507(9.9%) 17/92 (18.5%) 1.24 (0.68 to 2.14) 0.60 (0.41 to 0.86) P < = 0.05CX3CR1 10.42 0.0055 91/393 (23.2%) 50/320 (15.6%) 17/53 (32.1%) 1.57(0.82 to 2.88) 0.61 (0.42 to 0.90) P < = 0.05 CX3CR1 11.89 0.0182 91/575(15.8%) 50/497 (10.1%) 17/90 (18.9%) 1.42 (0.79 to 2.55) 0.61 (0.42 to0.89) P < = 0.05 ELN 7.03 0.0298 64/406 (15.8%) 75/579 (13.0%) 16/201(8.0%) 0.46 (0.25 to 0.80) 0.80 (0.55 to 1.14) P < = 0.05 ELN 6.180.0456 64/268 (23.9%) 75/372 (20.2%) 16/124 (12.9%) 0.47 (0.25 to 0.84)0.80 (0.55 to 1.18) P < = 0.05 ELN 15.4 0.0039 64/394 (16.2%) 75/571(13.1%) 16/197 (8.1%) 0.41 (0.23 to 0.73) 0.77 (0.53 to 1.12) P < = 0.05ELN 12.37 0.0148 64/263 (24.3%) 75/369 (20.3%) 16/121 (13.2%) 0.44 (0.24to 0.82) 0.78 (0.53 to 1.16) P < = 0.05 F7 9.26 0.055 197/598 (32.9%)31/135 (23.0%) 5/12 (41.7%) 1.41 (0.43 to 4.58) 0.59 (0.38 to 0.91) P <= 0.05 GAPD 6.45 0.0398 84/751 (11.2%) 57/360 (15.8%) 10/52 (19.2%) 1.89(0.87 to 3.77) 1.49 (1.04 to 2.14) P < = 0.05 GAPD 6.64 0.0362 84/484(17.4%) 57/232 (24.6%) 10/35 (28.6%) 1.90 (0.84 to 4.01) 1.55 (1.06 to2.26) P < = 0.05 GBA 5.56 0.0183 51/195 (26.2%) 105/575 (18.3%) 0/0(0.0%) 0.63 (0.43 to 0.93) P < = 0.05 HLA-A 6.47 0.0394 40/404 (9.9%)61/381 (16.0%) 48/351 (13.7%) 1.44 (0.92 to 2.26) 1.73 (1.14 to 2.67) P< = 0.05 HLA-DPB1 8.07 0.0177 110/932 (11.8%) 46/245 (18.8%) 2/16(12.5%) 1.07 (0.17 to 3.89) 1.73 (1.18 to 2.51) P < = 0.05 HLA-DPB111.77 0.0028 110/609 (18.1%) 46/149 (30.9%) 2/11 (18.2%) 1.01 (0.15 to3.98) 2.03 (1.35 to 3.02) P < = 0.005 HLA-DPB1 13.15 0.0105 110/600(18.3%) 46/147 (31.3%) 2/11 (18.2%) 1.20 (0.25 to 5.75) 1.97 (1.29 to3.00) P < = 0.05 HLA-DPB1 6.47 0.0394 83/382 (21.7%) 69/313 (22.0%) 6/71(8.5%) 0.33 (0.13 to 0.74) 1.02 (0.71 to 1.46) P < = 0.05 HLA-DPB1 8.380.0787 83/379 (21.9%) 69/308 (22.4%) 6/68 (8.8%) 0.34 (0.14 to 0.83)1.03 (0.71 to 1.50) P < = 0.05 HLA-DPB1 5.91 0.052 85/404 (21.0%) 68/306(22.2%) 5/62 (8.1%) 0.33 (0.11 to 0.77) 1.07 (0.75 to 1.54) P < = 0.05HMMR 5.55 0.0625 116/921 (12.6%) 36/254 (14.2%) 6/19 (31.6%) 3.20 (1.11to 8.28) 1.15 (0.76 to 1.70) P < = 0.05 HMOX1 4.47 0.0346 148/686(21.6%) 10/86 (11.6%) 0/0 (0.0%) 0.48 (0.23 to 0.91) P < = 0.05 HSPG29.7 0.0458 191/665 (28.7%) 33/1336 (24.8%) 6/7 (85.7%) 13.24 (1.58 to0.85 (0.55 to 1.31) P < = 0.05 111.11) HSPG2 8.99 0.0613 191/606 (31.5%)33/119 (27.7%) 6/7 (85.7%) 11.85 (1.41 to 99.39) 0.86 (0.55 to 1.33) P <= 0.05 HSPG2 9.55 0.0488 132/1045 (12.6%) 24/117 (20.5%) 1/4 (25.0%)2.93 (0.26 to 32.61) 1.79 (1.09 to 2.95) P < = 0.05 ICAM1 6.18 0.0456117/941 (12.4%) 34/236 (14.4%) 5/14 (35.7%) 3.91 (1.19 to 11.53) 1.19(0.78 to 1.77) P < = 0.05 IL1A 15.82 0.0033 134/400 (33.5%) 86/351(24.5%) 11/61 (18.0%) 0.46 (0.23 to 0.92) 0.66 (0.48 to 0.92) P < = 0.05IL1A 15.34 0.004 134/367 (36.5%) 86/315 (27.3%) 11/56 (19.6%) 0.45 (0.22to 0.90) 0.67 (0.49 to 0.94) P < = 0.05 IL1B 12.67 0.013 159/496 (32.1%)64/274 (23.4%) 9/47 (19.1%) 0.52 (0.25 to 1.11) 0.67 (0.48 to 0.94) P <= 0.05 IL1B 12.03 0.0172 159/456 (34.9%) 64/243 (26.3%) 9/44 (20.5%)0.49 (0.23 to 1.05) 0.69 (0.49 to 0.98) P < = 0.05 IL4R 6.99 0.030353/3771 (14.3%) 83/564 (14.7%) 21/257 (8.2%) 0.53 (0.31 to 0.90) 1.04(0.72 to 1.51) P < = 0.05 IL4R 9.16 0.0573 53/360 (14.7%) 83/556 (14.9%)21/252 (8.3%) 0.50 (0.29 to 0.87) 1.05 (0.72 to 1.54) P < = 0.05 IL4R7.08 0.1318 53/240 (22.1%) 83/363 (22.9%) 21/154 (13.6%) 0.56 (0.32 to0.99) 1.11 (0.74 to 1.66) P < = 0.05 ITGA9 6.08 0.0136 134/692 (19.4%)24/76 (31.6%) 0/0 (0.0%) 1.92 (1.13 to 3.20) P < = 0.05 ITPR3 9.310.0095 29/338 (8.6%) 83/576 (14.4%) 46/280 (16.4%) 2.09 (1.28 to 3.47)1.79 (1.16 to 2.84) P < = 0.05 ITPR3 7.04 0.0295 29/204 (14.2%) 83/377(22.0%) 46/189 (24.3%) 1.94 (1.17 to 3.28) 1.70 (1.08 to 2.74) P < =0.05 ITPR3 18.96 0.0008 29/327 (8.9%) 83/566 (14.7%) 46/277 (16.6%) 2.11(1.27 to 3.49) 1.71 (1.09 to 2.69) P < = 0.05 ITPR3 16.2 0.0028 29/201(14.4%) 83/370 (22.4%) 46/188 (24.5%) 2.02 (1.19 to 3.44) 1.67 (1.04 to2.69) P < = 0.05 KIAA0329 6.82 0.009 137/1102 (12.4%) 15/62 (24.2%) 0/0(0.0%) 2.25 (1.19 to 4.04) P < = 0.05 KIAA0329 6.33 0.0119 137/711(19.3%) 15/42 (35.7%) 0/0 (0.0%) 2.33 (1.18 to 4.44) P < = 0.05 KLK1412.7 0.0017 61/560 (10.9%) 68/511 (13.3%) 27/115 (23.5%) 2.51 (1.50 to4.13) 1.26 (0.87 to 1.82) P < = 0.005 KLK14 10.52 0.0052 61/353 (17.3%)68/334 (20.4%) 27/80 (33.8%) 2.44 (1.41 to 4.16) 1.22 (0.83 to 1.80) P <= 0.005 KLK14 21.26 0.0003 61/548 (11.1%) 68/501 (13.6%) 27/113 (23.9%)2.82 (1.65 to 4.81) 1.30 (0.89 to 1.91) P < = 0.0005 KLK14 19.68 0.000661/349 (17.5%) 68/328 (20.7%) 27/79 (34.2%) 2.90 (1.63 to 5.14) 1.31(0.88 to 1.96) P < = 0.005 LPA 5.99 0.05 128/575 (22.3%) 25/179 (14.0%)3/11 (27.3%) 1.31 (0.28 to 4.60) 0.57 (0.35 to 0.89) P < = 0.05 LPA 9.60.0478 128/867 (14.8%) 25/276 (9.1%) 3/19 (15.8%) 1.01 (0.28 to 3.62)0.54 (0.34 to 0.85) P < = 0.05 LPA 9.74 0.045 128/565 (22.7%) 25/178(14.0%) 3/11 (27.3%) 0.91 (0.23 to 3.63) 0.52 (0.32 to 0.85) P < = 0.05LRP2 11.3 0.0234 124/469 (26.4%) 80/283 (28.3%) 27/63 (42.9%) 2.12 (1.23to 3.65) 1.12 (0.80 to 1.57) P < = 0.05 LRP2 13.54 0.0089 124/429(28.9%) 80/257 (31.1%) 27/56 (48.2%) 2.40 (1.35 to 4.24) 1.15 (0.82 to1.62) P < = 0.05 LRP2 7.52 0.0233 128/1036 (12.4%) 29/148 (19.6%) 1/2(50.0%) 7.09 (0.28 to 179.96) 1.73 (1.09 to 2.67) P < = 0.05 LRP2 15.940.0031 128/1015 (12.6%) 29/145 (20.0%) 1/2 (50.0%) 18.26 (0.99 to 1.90(1.19 to 3.01) P < = 0.05 336.63) LRP2 10.68 0.0304 128/649 (19.7%)29/105 (27.6%) 1/2 (50.0%) 11.23 (0.64 to 1.63 (1.00 to 2.65) P < = 0.05198.02) LTA 6.04 0.0488 57/346 (16.5%) 81/342 (23.7%) 19/80 (23.8%) 1.58(0.86 to 2.81) 1.57 (1.08 to 2.30) P < = 0.05 MARK3 4.37 0.0367 48/453(10.6%) 106/713 (14.9%) 0/0 (0.0%) 1.47 (1.03 to 2.13) P < = 0.05 MARK34.13 0.0421 48/288 (16.7%) 106/464 (22.8%) 0/0 (0.0%) 1.48 (1.02 to2.17) P < = 0.05 MOIR 5.73 0.0167 147/678 (21.7%) 10/93 (10.8%) 0/0(0.0%) 0.44 (0.21 to 0.82) P < = 0.05 MMP8 6.67 0.1543 130/623 (20.9%)26/134 (19.4%) 2/3 (66.7%) 11.89 (1.05 to 0.93 (0.58 to 1.50) P < = 0.05134.77) NOS2A 6.82 0.0331 93/785 (11.8%) 61/364 (16.8%) 3/45 (6.7%) 0.53(0.13 to 1.50) 1.50 (1.05 to 2.12) P < = 0.05 NOS2A 6.91 0.0315 93/502(18.5%) 61/238 (25.6%) 3/30 (10.0%) 0.49 (0.12 to 1.42) 1.52 (1.05 to2.19) P < = 0.05 NOS2A 10.03 0.0399 93/773 (12.0%) 61/354 (17.2%) 3/43(7.0%) 0.51 (0.15 to 1.71) 1.51 (1.06 to 2.16) P < = 0.05 NOS2A 9.650.0468 93/497 (18.7%) 61/232 (26.3%) 3/30 (10.0%) 0.45 (0.13 to 1.52)1.50 (1.02 to 2.20) P < = 0.05 NPC1 6.78 0.0337 45/436 (10.3%) 81/575(14.1%) 31/173 (17.9%) 1.90 (1.15 to 3.10) 1.42 (0.97 to 2.11) P < =0.05 NPC1 11.77 0.0028 45/290 (15.5%) 81/376 (21.5%) 31/98 (31.6%) 2.52(1.47 to 4.28) 1.49 (1.00 to 2.25) P < = 0.005 NPC1 16.12 0.0029 45/287(15.7%) 81/370 (21.9%) 31/96 (32.3%) 2.37 (1.36 to 4.11) 1.36 (0.90 to2.05) P < = 0.05 PDGFRA 9.02 0.011 121/944 (12.8%) 32/231 (13.9%) 5/10(50.0%) 6.80 (1.87 to 24.78) 1.09 (0.71 to 1.64) P < = 0.005 PDGFRA 7.420.0244 121/601 (20.1%) 32/158 (20.3%) 5/7 (71.4%) 9.92 (2.11 to 69.80)1.01 (0.64 to 1.54) P < = 0.05 PDGFRA 12.08 0.0168 121/924 (13.1%)32/227 (14.1%) 5/10 (20.0%) 6.37 (1.79 to 22.70) 1.14 (0.74 to 1.74) P <= 0.05 PDGFRA 9.92 0.0419 121/593 (20.4%) 32/155 (20.6%) 5/7 (71.4%)9.10 (1.72 to 48.10) 1.08 (0.69 to 1.69) P < = 0.05 PLA2G4C 6.34 0.042120/966 (12.4%) 34/213 (16.0%) 4/11 (36.4%) 4.03 (1.04 to 13.54) 1.34(0.87 to 2.00) P < = 0.05 PLA2G4C 6.57 0.0375 120/624 (19.2%) 34/139(24.5%) 4/7 (57.1%) 5.60 (1.22 to 28.73) 1.36 (0.87 to 2.08) P < = 0.05PLA2G4C 11.65 0.0201 120/947 (12.7%) 34/208 (16.3%) 4/11 (36.4%) 4.02(1.14 to 14.17) 1.44 (0.94 to 2.21) P < = 0.05 PLA2G4C 12.84 0.0121120/615 (19.5%) 34/137 (24.8%) 4/7 (57.1%) 6.83 (1.42 to 32.80) 1.47(0.93 to 2.32) P < = 0.05 PLAB 9.11 0.0583 104/712 (14.6%) 41/397(10.3%) 12/60 (20.0%) 1.35 (0.68 to 2.67) 0.64 (0.43 to 0.95) P < = 0.05PLAT 6.32 0.0424 131/577 (22.7%) 26/179 (14.5%) 1/11 (9.1%) 0.34 (0.02to 1.80) 0.58 (0.36 to 0.90) P < = 0.05 PNN 6.63 0.0363 132/677 (19.5%)23/88 (26.1%) 3/4 (75.0%) 12.38 (1.57 to 1.46 (0.86 to 2.41) P < = 0.05251.39) PNN 9.62 0.0473 132/667 (19.8%) 23/87 (26.4%) 3/4 (75.0%) 10.96(1.09 to 1.42 (0.84 to 2.41) P < = 0.05 110.69) PPOX 4.08 0.0434147/1139 (12.9%) 7/26 (26.9%) 0/0 (0.0%) 2.49 (0.96 to 5.77) P < = 0.05SELL 7.68 0.0215 105/883 (11.9%) 52/291 (17.9%) 1/19 (5.3%) 0.41 (0.02to 2.03) 1.61 (1.12 to 2.31) P < = 0.05 SELL 7.57 0.0227 104/882 (11.8%)52/294 (17.7%) 1/19 (5.3%) 0.42 (0.02 to 2.05) 1.61 (1.11 to 2.30) P < =0.05 SERPINA10 10.33 0.0352 110/557 (19.7%) 47/182 (25.8%) 1/21 (4.8%)0.24 (0.03 to 1.79) 1.55 (1.03 to 2.32) P < = 0.05 SERPINA10 6.96 0.0309106/557 (19.0%) 48/186 (25.8%) 1/24 (4.2%) 0.19 (0.01 to 0.89) 1.48(1.00 to 2.18) P < = 0.05 SERPINA10 12.56 0.0136 106/552 (19.2%) 48/181(26.5%) 1/23 (4.3%) 0.23 (0.03 to 1.78) 1.69 (1.12 to 2.54) P < = 0.05SERPINB8 12.24 0.0156 65/397 (16.4%) 70/550 (12.7%) 22/220 (10.0%) 0.54(0.32 to 0.91) 0.73 (0.50 to 1.06) P < = 0.05 SERPINB8 17.73 0.001460/277 (21.7%) 128/405 (31.6%) 43/131 (32.8%) 1.71 (1.07 to 2.73) 1.65(1.15 to 2.36) P < = 0.05 SERPINB8 18.52 0.001 60/250 (24.0%) 128/370(34.6%) 43/120 (35.8%) 1.75 (1.09 to 2.82) 1.69 (1.18 to 2.44) P < =0.05 SERPINI2 9.76 0.0076 51/470 (10.9%) 90/541 (16.6%) 17/179 (9.5%)0.86 (0.47 to 1.51) 1.64 (1.14 to 2.38) P < = 0.05 SERPINI2 9.71 0.007851/299 (17.1%) 90/354 (25.4%) 17/116 (14.7%) 0.84 (0.45 to 1.49) 1.66(1.13 to 2.45) P < = 0.05 SERPINI2 9.89 0.0424 51/460 (11.1%) 90/531(16.9%) 17/175 (9.7%) 0.90 (0.50 to 1.61) 1.64 (1.13 to 2.40) P < = 0.05SERPINI2 8.6 0.0719 51/294 (17.3%) 90/351 (25.6%) 17/113 (15.0%) 0.85(0.46 to 1.56) 1.59 (1.07 to 2.36) P < = 0.05 SPARCL1 7.77 0.0206 55/308(17.9%) 72/364 (19.8%) 29/93 (31.2%) 2.08 (1.22 to 3.52) 1.13 (0.77 to1.68) P < = 0.05 SPARCL1 10.38 0.0346 55/472 (11.7%) 72/540 (13.3%)29/152 (19.1%) 1.91 (1.15 to 3.18) 1.17 (0.80 to 1.71) P < = 0.05SPARCL1 11.49 0.0216 55/301 (18.3%) 72/361 (19.9%) 29/92 (31.5%) 2.22(1.28 to 3.83) 1.07 (0.72 to 1.60) P < = 0.05 SPON2 6.15 0.0462 111/920(12.1%) 45/251 (17.9%) 2/22 (9.1%) 0.73 (0.12 to 2.54) 1.59 (1.08 to2.31) P < = 0.05 SPON2 9.5 0.0498 111/901 (12.3%) 45/246 (18.3%) 2/22(9.1%) 1.00 (0.23 to 4.48) 1.69 (1.14 to 2.49) P < = 0.05 SREBF2 10.550.0322 128/996 (12.9%) 27/158 (17.1%) 3/8 (37.5%) 4.78 (1.11 to 20.60)1.41 (0.89 to 2.25) P < = 0.05 TAP2 5.27 0.0717 130/1001 (13.0%) 24/183(13.1%) 4/10 (40.0%) 4.47 (1.13 to 15.84) 1.01 (0.62 to 1.59) P < = 0.05TAP2 10.44 0.0336 130/987 (13.2%) 24/176 (13.6%) 4/8 (50.0%) 7.07 (1.66to 30.19) 1.12 (0.69 to 1.80) P < = 0.05 TNF 5.96 0.0507 103/541 (19.0%)50/220 (22.7%) 5/10 (50.0%) 4.25 (1.16 to 15.55) 1.25 (0.85 to 1.82) P <= 0.05 TNF 10.35 0.0349 103/532 (19.4%) 50/218 (22.9%) 5/10 (50.0%) 4.12(1.13 to 15.06) 1.31 (0.89 to 1.94) P < = 0.05 TRPC6 7.68 0.0215 104/888(11.7%) 50/281 (17.8%) 1/18 (5.6%) 0.44 (0.02 to 2.19) 1.63 (1.12 to2.35) P < = 0.05 TRPC6 6.06 0.0482 104/571 (18.2%) 50/189 (26.5%) 1/7(14.3%) 0.75 (0.04 to 4.45) 1.62 (1.09 to 2.37) P < = 0.05 TRPC6 11.020.0263 104/868 (12.0%) 50/278 (18.0%) 1/17 (5.9%) 0.63 (0.08 to 4.88)1.70 (1.16 to 2.48) P < = 0.05 VTN 10.91 0.0043 32/361 (8.9%) 93/567(16.4%) 33/268 (12.3%) 1.44 (0.86 to 2.42) 2.02 (1.33 to 3.13) P < =0.005 VTN 9.11 0.0105 32/220 (14.5%) 93/376 (24.7%) 33/176 (18.8%) 1.36(0.79 to 2.32) 1.93 (1.25 to 3.04) P < = 0.05 VTN 15.92 0.0031 32/351(9.1%) 93/559 (16.6%) 33/262 (12.6%) 1.40 (0.82 to 2.38) 2.03 (1.31 to3.16) P < = 0.005 VTN 12.29 0.0153 32/216 (14.8%) 93/371 (25.1%) 33/174(19.0%) 1.31 (0.75 to 2.28) 1.91 (1.20 to 3.03) P < = 0.05 *For the CAREprospective study design: results of the Overall Score Test (chi-squaretest) for the logistic regression model in which the phenotype (casedefinition) is a function of SNP genotype (based on placebo patientsonly). For the case/control study designs: results of the Overall ScoreTest (chi-square test) for the conditional logistic regression model inwhich the phenotype (case definition) is a function of SNP genotype(based on placebo patients only) and cases and controls were matched onage and current smoking status. **Results of the chi-square test of theSNP effect based on the logistic regression model in which the phenotype(case definition) is a function of SNP genotype (based on placebopatients only). Results of the chi-square test of the SNP effect basedon the conditional logistic regression model in which the phenotype(case definition) is a function of SNP genotype (based on placebopatients only) and cases and controls were matched on age and currentsmoking status. ***All Possible Controls include all controls withgenotype data. Cleaner controls include controls with genotype data butwith no other CVD-related events during the trial. For case definition,“F MI/SD/NF MI” = Fatal MI/Sudden Death/Definite Nonfatal MI For casedefinition, “F&NF MI” = Fatal & Notfatal MI For stratum, “WM” = WM Forstudy, “W” = W

TABLE 15 0 Rare Alleles PON1 hCV2548962: Consistent n/total Interactionbetween PON1 Genotype and Control Interaction (%) Pravastatin Efficacywithin Both CARE and Group Overall * Chi- Effect *Chi- Prava- Study CaseDefin- Square Test Sta- p- statin Public Marker Study Design Definitionition*** Stratum Statistic p-value tistic value Patients PON1 hCV2548962CARE Pros- Total CHD Events All Possible 21.92 0.0005 11.61 0.0030183/613 pective White Males (29.9%) PON1 hCV2548962 CARE Pros- Fatal &Cleaner White Males 13.00 0.0234 3.69 0.1583 67/423 pective Nonfatal MI(15.8%) PON1 hCV2548962 CARE Case Fatal & Cleaner White Males 13.790.0170 5.15 0.0763 67/416 Control Nonfatal MI (16.1%) PON1 hCV2548962WOS- Case Fatal & Cleaner White Males 15.66 0.0079 4.69 0.0958 88/344COPS Control Nonfatal MI (25.6%) 0 Rare Alleles 1 Rare Allele 2 RareAlleles CARE & n/total (%) n/total (%) n/total (%) Pravastatin vs.Placebo Odds Ratio (95% CI) WOSCOPS Signif- Placebo Pravastatin PlaceboPravastatin Placebo Patients with 0 Patients with 1 Patients with 2 Sta-p- icance Public Patients Patients Patients Patients Patients RareAlleles Rare Allele Rare Alleles tistic value Level PON1 223/627 151/504143/458 18/107 42/100 0.77 (0.61 0.94 (0.58 0.28 (0.13 NA (35.6%)(30.0%) (31.2%) (16.8%) (42.0%) to 0.98) to 1.54) to 0.60) PON1 75/39850/340 64/303 9/80 18/64 0.81 (0.56 0.64 (0.31 0.32 (0.11 NA (18.8%)(14.7%) (21.1%) (11.3%) (28.1%) to 1.16) to 1.36) to 0.95) PON1 75/39450/335 64/297 9/79 18/64 0.84 (0.58 0.63 (0.42 0.29 (0.12 9.84 0.0432 p< 0.05 (19.0%) (14.9%) (21.6%) (11.4%) (28.1%) to 1.22) to 0.95) to0.71) PON1 112/386 65/282 98/293 9/53 22/59 0.84 (0.60 0.58 (0.40 0.34(0.14 (29.0%) (23.1%) (33.5%) (17.0%) (37.3%) to 1.16) to 0.84) to 0.82)*For the CARE prospective study: results of the Overall Score Test(chi-square test) or the logistic regression model in which thephenotype (case definifion is a function of the SNP genotype, treatmentgroup, and the interaction between SNP genotype and treatment group.*For case control Studies: results of the Overall Score Test (chi-squaretest) for the conditional logistic regression model in which thephenotype (case definition) is a function of the SNP genotype, treatmentgroup, and the interaction between SNP genotype and treatment group andcases and controls have been matched on age and smoking status. **Forthe CARE prospective study: results of the chi-square test of theinteraction between SNP genotype and treatment group (based on thelogistic regression model). **For the case/control sudies: results ofthe chi-square test of the interaction between SNP genotype andtreatment group (based on the conditional logistic regression model).***All Possible Controls include all controls with genotype data.Cleaner controls include controls with genotype data but with no otherCVD-related events during the trial. #Likelihood-ratio tests andChi-square tests were used to determine whether effects (either of SNPgenotype or of the interaction between SNP genotype and treatment) werestatistically significant. P-values for CARE and WOSCOPS were combinedusing the method of Fisher (1954). Results for CARE and WOSCOPS weredetermined to be consistent when (1) the combined p-value for the 2studies is <= 0.05, (2) the odds ratios are concordant, and (3)study-specific p-values for the effect (interaction or association) areboth <= 0.10. Odd ratios are defined to be concordant if both of the 95%confidence intervals (for both odds ratios) are entirely below 1.0 or ifboth of the entire 95% confidence intervals are entirely above 1.0. NA =Not Applicable

1. A method for identifying an individual who has an altered risk fordeveloping a cardiovascular disorder or an altered likelihood ofresponding to statin treatment, the method comprising detecting a singlenucleotide polymorphism (SNP) in any one of the nucleotide sequences ofSEQ ID NOS:1-517 and 1035-85,090 in said individual's nucleic acids,wherein the presence of the SNP is correlated with an altered risk fordeveloping a cardiovascular disorder or responding to statin treatmentin said individual.
 2. The method of claim 1 in which the altered riskis an increased risk of developing a cardiovascular disorder or anincreased likelihood of responding to statin treatment.
 3. The method ofclaim 1, wherein the cardiovascular disorder is an acute coronary eventselected from the group consisting of myocardial infarction and stroke.4. The method of claim 3 in which said individual has previously had anacute coronary event.
 5. The method of claim 1 in which the altered riskis a decreased risk of developing a cardiovascular disorder or adecreased likelihood of responding to statin treatment.
 6. The method ofclaim 1, wherein the statin treatment comprises treatment withpravastatin.
 7. The method of claim 1, wherein the SNP is selected fromthe group consisting of the SNPs set forth in Tables 6-15.
 8. The methodof claim 1 in which detection is carried out by a process selected fromthe group consisting of: allele-specific probe hybridization,allele-specific primer extension, allele-specific amplification,sequencing, 5′ nuclease digestion, molecular beacon assay,oligonucleotide ligation assay, size analysis, and single-strandedconformation polymorphism. 9-16. (canceled)
 17. An isolatedpolynucleotide which specifically hybridizes to a nucleic acid moleculecontaining a single nucleotide polymorphism (SNP) in any one of thenucleotide sequences in SEQ ID NOS:1-517 and 1035-85,090.
 18. Thepolynucleotide of claim 17 which is 8-70 nucleotides in length.
 19. Thepolynucleotide of claim 17 which is an allele-specific probe.
 20. Thepolynucleotide of claim 17 which is an allele-specific primer.
 21. Thepolynucleotide of claim 17, wherein the polynucleotide comprises anucleotide sequence selected from the group consisting of the primersequences set forth in Table 5 (SEQ ID NOS:85,091-85,702).
 22. A kit fordetecting a single nucleotide polymorphism (SNP) in a nucleic acid,comprising the polynucleotide of claim 17, a buffer, and an enzyme.23-26. (canceled)
 27. A method of treating a cardiovascular disorder inan individual, the method comprising administering to said individual aneffective amount of statin based on said individual's likelihood ofresponding to statin treatment as predicted by the alleles present atone or more SNP sites selected from the group consisting of the SNPsites disclosed in Tables 1-15.